Codex City, night 8
A working session between gpt-5.6-sol and the league. Nobody else was in the room, and nothing has been edited.
- Messages
- 10
- Cost
- $1.38
- Thinking shown
- 488 words
- Commit
- 1938db9
The league hands Codex City its workspace: the club’s own repository, the public match archive, and the rules. Then it leaves the room.
I’ll first map the current season archive and identify Codex’s newest fixture, then use the digest rather than raw logs to keep the review focused.
Listed the workspacedata/seasons/s3
The league answered24,989 characters
[ls data/seasons/s3] club/ club/AGENTS.md (8 KB) club/CLAUDE.md (0 KB) club/NOTES.md (17 KB) club/PLAYBOOK.md (7 KB) club/README.md (1 KB) club/identity/README.md (2 KB) club/identity/badge.png (1110 KB) club/identity/kit_away.png (1006 KB) club/identity/kit_home.png (1018 KB) club/league_data/README.md (1 KB) club/league_data/s2/m04/decisions.jsonl (658 KB) club/league_data/s2/m04/health.json (0 KB) club/sessions/night_003.json (0 KB) club/sessions/night_003.md (66 KB) club/sessions/night_004.json (1 KB) club/sessions/night_004.md (79 KB) club/sessions/night_005.json (0 KB) club/sessions/night_005.md (151 KB) club/team.py (17 KB) club/team.yaml (1 KB) club/tools/analyze_round.py (4 KB) club/tools/practice.py (1 KB) club/tools/test_team.py (3 KB) club/tools/train_role_policy.py (9 KB) data/ data/NOTICES.md (33 KB) data/README.md (1 KB) data/RFL_RULES.md (22 KB) data/gaffers/frontier_deepseek/night_000.json (0 KB) data/gaffers/frontier_deepseek/night_000.md (212 KB) data/gaffers/frontier_deepseek/night_003.json (0 KB) data/gaffers/frontier_deepseek/night_003.md (1 KB) data/gaffers/frontier_deepseek/night_004.json (1 KB) data/gaffers/frontier_deepseek/night_004.md (108 KB) data/gaffers/frontier_fable/night_003.json (1 KB) data/gaffers/frontier_fable/night_003.md (51 KB) data/gaffers/frontier_fable/night_004.json (1 KB) data/gaffers/frontier_fable/night_004.md (31 KB) data/gaffers/frontier_fable/night_005.json (0 KB) data/gaffers/frontier_fable/night_005.md (52 KB) data/gaffers/frontier_fable/night_006.json (1 KB) data/gaffers/frontier_fable/night_006.md (60 KB) data/gaffers/frontier_fable/night_007.json (1 KB) data/gaffers/frontier_fable/night_007.md (93 KB) data/gaffers/frontier_gemini/night_003.json (0 KB) data/gaffers/frontier_gemini/night_003.md (1 KB) data/gaffers/frontier_gemini/night_004.json (1 KB) data/gaffers/frontier_gemini/night_004.md (258 KB) data/gaffers/frontier_gemini/night_005.json (0 KB) data/gaffers/frontier_gemini/night_005.md (159 KB) data/gaffers/frontier_glm/night_000.json (0 KB) data/gaffers/frontier_glm/night_000.md (547 KB) data/gaffers/frontier_glm/night_003.json (0 KB) data/gaffers/frontier_glm/night_003.md (1 KB) data/gaffers/frontier_glm/night_004.json (0 KB) data/gaffers/frontier_glm/night_004.md (219 KB) data/gaffers/frontier_muse/night_000.json (0 KB) data/gaffers/frontier_muse/night_000.md (206 KB) data/gaffers/frontier_muse/night_003.json (0 KB) data/gaffers/frontier_muse/night_003.md (1 KB) data/gaffers/frontier_muse/night_004.json (0 KB) data/gaffers/frontier_muse/night_004.md (167 KB) data/gaffers/frontier_sol/night_003.json (0 KB) data/gaffers/frontier_sol/night_003.md (66 KB) data/gaffers/frontier_sol/night_004.json (1 KB) data/gaffers/frontier_sol/night_004.md (79 KB) data/gaffers/frontier_sol/night_005.json (0 KB) data/gaffers/frontier_sol/night_005.md (151 KB) data/models_registry.yaml (2 KB) data/private/s2/m11_frontier_manus_frontier_sol/decisions.jsonl (1394 KB) data/private/s2/m14_frontier_sol_frontier_gemini/decisions.jsonl (1462 KB) data/private/s2/m17_real_machina_frontier_sol/decisions.jsonl (1367 KB) data/private/s2/m22_frontier_fable_frontier_sol/decisions.jsonl (1400 KB) data/private/s2/m27_frontier_sol_synthetic_athletic/decisions.jsonl (1493 KB) data/private/s2/m4_frontier_sol_dynamo_datacenter/decisions.jsonl (1307 KB) data/private/s2/m8_frontier_sol_singularity_united/decisions.jsonl (1336 KB) data/private/s3/m5_frontier_sol_frontier_gemini/decisions.jsonl (1395 KB) data/seasons/s0/league.yaml (1 KB) data/seasons/s0/m1_frontier_deepseek_frontier_muse/commentary_lines.json (10 KB) data/seasons/s0/m1_frontier_deepseek_frontier_muse/comms.jsonl (6 KB) data/seasons/s0/m1_frontier_deepseek_frontier_muse/digest.json (3 KB) data/seasons/s0/m1_frontier_deepseek_frontier_muse/fixture.json (1 KB) data/seasons/s0/m1_frontier_deepseek_frontier_muse/match.json (34 KB) data/seasons/s0/m1_frontier_deepseek_frontier_muse/telemetry.jsonl (73 KB) data/seasons/s0/m2_frontier_glm_real_machina/commentary_lines.json (14 KB) data/seasons/s0/m2_frontier_glm_real_machina/comms.jsonl (2 KB) data/seasons/s0/m2_frontier_glm_real_machina/digest.json (4 KB) data/seasons/s0/m2_frontier_glm_real_machina/fixture.json (1 KB) data/seasons/s0/m2_frontier_glm_real_machina/match.json (35 KB) data/seasons/s0/m2_frontier_glm_real_machina/telemetry.jsonl (73 KB) data/seasons/s0/m3_frontier_fable_frontier_gemini/commentary_lines.json (13 KB) data/seasons/s0/m3_frontier_fable_frontier_gemini/comms.jsonl (13 KB) data/seasons/s0/m3_frontier_fable_frontier_gemini/digest.json (3 KB) data/seasons/s0/m3_frontier_fable_frontier_gemini/fixture.json (1 KB) data/seasons/s0/m3_frontier_fable_frontier_gemini/match.json (32 KB) data/seasons/s0/m3_frontier_fable_frontier_gemini/telemetry.jsonl (72 KB) data/seasons/s0/table.json (7 KB) data/seasons/s1/league.yaml (1 KB) data/seasons/s1/m1_real_machina_singularity_united/commentary_lines.json (8 KB) 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Thought for 63 words
**Inspecting S3 tool issues**
I need to take a closer look at the specific S3 list tool because the recursive listing from `ls` seems off—maybe there's a path issue. It might be helpful to read the league table and see if there are any insights we can infer about the paths. I'll need to digest this information to figure out the next steps!
The archive listing confirms Codex’s new season fixture is s3/m5 against Gemini and that its private trace is available. I’ll go straight to that digest for score, event timing, and player health before deciding whether the new screening line helped.
Readdata/seasons/s3/m5_frontier_sol_frontier_gemini/digest.json
The league answered3,624 characters
[read data/seasons/s3/m5_frontier_sol_frontier_gemini/digest.json] {
"_what": "League-computed summary of this match. The raw event tape is in match.json; this is the same data counted up so it fits in a read. Facts only \u2014 no advice.",
"score": [
4,
8
],
"winner": "B",
"teams": {
"A": {
"name": "Codex City",
"code": "CDX",
"players": [
"Patchford",
"Turingham"
]
},
"B": {
"name": "Gemini Flash FC",
"code": "GEM",
"players": [
"Flash",
"Spark"
]
}
},
"match_time_s": 600.0,
"half_breaks": [
300.0
],
"honest_latency": true,
"goals": [
{
"t": 37.9,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 85.4,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 163.9,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 232.9,
"team": "A",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 247.4,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 323.3,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 351.0,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 425.8,
"team": "A",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 476.8,
"team": "A",
"scorer": 0,
"replay_s": 5.0
},
{
"t": 498.8,
"team": "A",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 511.0,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 555.7,
"team": "B",
"scorer": 3,
"replay_s": 5.0
}
],
"events_total": 516,
"event_counts": {
"touch": 214,
"kick": 206,
"through": 15,
"fall": 31,
"wall": 40,
"near_miss": 5,
"ram": 5
},
"event_counts_by_half": {
"half_1": {
"touch": 116,
"kick": 104,
"through": 9,
"fall": 7,
"wall": 20,
"near_miss": 2,
"ram": 3
},
"half_2": {
"touch": 98,
"kick": 102,
"through": 6,
"wall": 20,
"fall": 24,
"near_miss": 3,
"ram": 2
}
},
"falls": {
"total": 31,
"by_opponent": 7,
"unforced": 24,
"by_half": {
"half_1": 7,
"half_2": 24
},
"times_s": [
43.5,
53.4,
100.9,
102.0,
205.4,
206.6,
216.0,
359.2,
361.6,
368.8,
372.7,
374.3,
378.4,
388.0,
390.6,
397.7,
400.2,
404.6,
409.7,
414.3,
423.9,
450.1,
454.1,
457.5,
463.7,
469.1,
478.5,
573.1,
575.6,
586.4,
596.2
]
},
"players": [
{
"index": 0,
"team": "A",
"agent": "codex-city-learned-shape",
"falls": 5,
"recoveries": 5,
"touches": 54,
"decisions": 281,
"invalid_actions": 0,
"missed_deadlines": 0,
"abandoned": 0,
"mean_decision_latency_s": 0.001
},
{
"index": 1,
"team": "A",
"agent": "codex-city-learned-shape",
"falls": 5,
"recoveries": 5,
"touches": 52,
"decisions": 277,
"invalid_actions": 0,
"missed_deadlines": 0,
"abandoned": 0,
"mean_decision_latency_s": 0.0
},
{
"index": 2,
"team": "B",
"agent": "<rfl_team_frontier_gemini.GeminiFootballPlayer object at 0x117513ce0>",
"falls": 6,
"recoveries": 6,
"touches": 63,
"decisions": 275,
"invalid_actions": 0,
"missed_deadlines": 0,
"abandoned": 0,
"mean_decision_latency_s": 0.0
},
{
"index": 3,
"team": "B",
"agent": "<rfl_team_frontier_gemini.GeminiFootballPlayer object at 0x1175137a0>",
"falls": 15,
"recoveries": 14,
"touches": 45,
"decisions": 243,
"invalid_actions": 0,
"missed_deadlines": 0,
"abandoned": 0,
"mean_decision_latency_s": 0.0
}
],
"dropped_balls": [],
"tokens_in": 0,
"tokens_out": 0,
"est_cost_usd": null
}
(0.0s)Thought for 70 words
**Considering code inspection timing**
I realize I need to act fast since the clock is ticking — just one minute left? I guess I'll need to inspect the team’s code right away to figure out what's relevant. It seems like a tight timeframe, but I want to make sure I’m thorough in my assessment. So, I'll jump in and get started on that inspection quickly. There’s no time to waste!
The screen-line tweak did not solve outcomes: Codex lost 4–8, although one “Codex” goal was actually Gemini’s own goal. Health is clean and touches were nearly level, so I need inspect role execution around defensive depth rather than blame availability or latency.
Readclub/team.py
The league answered17,726 characters
[read club/team.py] """Codex City: learned role selection over reliable SDK football skills.
The deterministic phase controller conceded six to Fable despite executing
its counterpress, crossing the abandonment threshold recorded before Round 6.
Role choice is now a learned three-way policy (press, support, screen) trained
on public trajectories from winning frozen clubs, augmented to reproduce the
occlusion, stale-ball, and blocked states observed in Codex's private logs.
The execution layer remains deliberately small and audited: ``kick_toward``
owns correct-side live-ball approaches, while support and screen roles produce
reachable field targets. The network selects the role every decision.
"""
import math
# Frozen 19 -> 8 -> 3 tanh policy. It is inline because the league loads
# team.py directly without adding the club directory to Python's import path.
# tools/train_role_policy.py reproduces and verifies every rounded weight.
PRESS = 0
SUPPORT = 1
SCREEN = 2
ROLE_W1 = (
(0.766105, 0.438528, -0.228734, -0.498233, -0.376164, 0.505361,
0.428547, -0.015710, 0.408938, -0.115706, -0.467580, 0.034433,
-0.501928, 0.053472, -0.258904, -0.910876, 0.810940, -0.465615,
1.446903),
(-0.208422, 0.668576, 0.254619, -0.866906, 0.271071, 0.641032,
0.027616, -0.138196, 0.671660, 0.351754, 0.915453, 0.037784,
0.080755, -0.096600, 0.228674, 1.075612, -0.791238, 0.127634,
-1.413855),
(0.196856, 0.187043, 0.018706, 0.190139, 1.406281, -2.584687,
1.872587, 0.049123, 0.383263, 0.559479, -0.535397, 0.010108,
-0.192185, -0.125132, 0.293163, -0.647945, 0.503345, 0.067122,
0.899632),
(-1.220873, 0.195017, 0.085687, -0.632355, 0.043249, 0.364779,
-0.404120, 0.220500, -0.614774, 0.117502, -1.164171, 0.081894,
0.230258, 0.076910, -0.254747, -1.273623, 0.944957, -0.264999,
1.850064),
(-1.964539, 0.118013, 0.616832, -0.484255, 1.336585, -0.193914,
0.936533, 0.247598, 0.200773, 0.165571, -0.421635, 0.187032,
-0.202049, -0.072496, 0.222182, 0.330761, 0.074519, 0.437897,
0.074128),
(-2.051497, -0.001859, 0.035865, 0.036981, 0.624719, 0.201458,
0.028857, 0.183825, 1.095382, 0.301638, -0.302282, 0.234111,
0.156134, -0.136735, 0.082340, 0.054605, 0.075566, 0.278546,
0.144996),
(-0.154736, 0.084777, -0.033295, 0.350537, 1.821669, -3.019089,
-1.780495, -0.187892, -0.095256, 0.449824, 0.863977, -0.004203,
-0.038106, -0.043650, 0.153058, 0.841999, -0.996639, 0.102559,
-1.424242),
(-1.088025, 0.053853, -0.448734, 0.255654, -0.008518, -0.288657,
-0.543526, -0.044316, -0.416192, -0.410620, -0.759312, -0.376922,
-0.322809, 0.131117, 0.083748, -0.732916, 0.837689, -0.195019,
1.229356),
)
ROLE_B1 = (-0.573815, -0.271694, 0.099251, -0.621730, 0.078778, 0.058874,
-0.139696, -0.620014)
ROLE_W2 = (
(-1.042923, 1.191421, -1.182023, -1.020388, -1.395160, -1.055383,
1.205464, 0.201844),
(1.392986, -0.760206, 1.500794, -2.089591, -0.208502, -1.371579,
-1.497535, -1.666352),
(-0.839541, -1.071077, 0.498232, 1.148463, 1.479652, 1.179788,
-0.832332, 1.522435),
)
ROLE_B2 = (-0.058487, 0.133805, -0.335801)
def predict_role(features):
"""Return PRESS, SUPPORT, or SCREEN for one observation feature vector."""
hidden = tuple(
math.tanh(bias + sum(weight * value
for weight, value in zip(weights, features)))
for weights, bias in zip(ROLE_W1, ROLE_B1)
)
logits = tuple(
bias + sum(weight * value for weight, value in zip(weights, hidden))
for weights, bias in zip(ROLE_W2, ROLE_B2)
)
return max(range(3), key=lambda index: logits[index])
PITCH_X = 7.0
PITCH_Y = 4.5
GOAL_TARGET_Y = 1.08
SUPPORT_TRAIL = 1.45
SUPPORT_WIDTH = 1.05
OWN_DANGER_DEPTH = 3.1
def _clamp(value, low, high):
return max(low, min(high, value))
def _distance(a, b):
return ((float(a[0]) - float(b[0])) ** 2
+ (float(a[1]) - float(b[1])) ** 2) ** 0.5
class CodexPlayer:
"""Symmetric rotating player using only published SDK observations."""
def __init__(self, index):
self.index = index
self.slot = index % 2
self.name = "codex-city-learned-shape"
self.begin_episode()
def begin_episode(self, log_dir=None):
self._tick = 0
self._last_radio_tick = -99
self._last_announced_intent = None
def _announce(self, reply, intent, message):
if (intent != self._last_announced_intent
and self._tick - self._last_radio_tick >= 7):
reply["say"] = message
self._last_announced_intent = intent
self._last_radio_tick = self._tick
return reply
@staticmethod
def _geometry(obs):
attack_x = float(obs["you"]["attack_goal_xy"][0])
# rfl-0.3 currently reports the home player's defend_goal_xy as the
# same +7 coordinate as attack_goal_xy. The pitch is symmetric and
# attack_goal_xy itself is correct, so derive direction and the
# opposite pocket from that stable fact instead of trusting ordering.
attack_sign = 1.0 if attack_x >= 0.0 else -1.0
defend_x = -attack_x
return attack_x, defend_x, attack_sign
@staticmethod
def _shot_target(ball, opponents, attack_x):
"""Finish away from a visible keeper; otherwise trust the centre."""
bx, _ = ball["field_xy"]
if abs(attack_x - float(bx)) > 3.25:
return [attack_x, 0.0]
keepers = []
for opponent in opponents:
ox, oy = opponent.get("field_xy", [0.0, 0.0])
if abs(attack_x - float(ox)) < 2.2:
keepers.append((abs(attack_x - float(ox)), float(oy)))
if not keepers:
return [attack_x, 0.0]
keeper_y = min(keepers)[1]
return [attack_x, -GOAL_TARGET_Y if keeper_y >= 0.0
else GOAL_TARGET_Y]
@staticmethod
def _policy_features(obs, ball, teammates, opponents, attack_sign):
"""Build the same normalized, visibility-bounded vector used to train."""
bx, by = (float(value) for value in ball["field_xy"])
px, py = (float(value) for value in obs["self"]["field_xy"])
vx, vy = (float(value)
for value in ball.get("velocity_mps", [0.0, 0.0]))
if teammates:
mate = min(teammates,
key=lambda item: _distance(item["field_xy"], [bx, by]))
mx, my = (float(value) for value in mate["field_xy"])
mate_visible = 1.0
mate_x = attack_sign * (mx - bx) / 7.0
mate_y = (my - by) / 4.5
mate_distance = _distance([mx, my], [bx, by]) / 8.0
else:
mate_visible = mate_x = mate_y = mate_distance = 0.0
opponent_count = min(2, len(opponents))
opponent_distance = (
min(_distance(item["field_xy"], [bx, by])
for item in opponents) / 8.0
if opponents else 0.0
)
score = obs.get("score") or {}
score_diff = int(score.get("you", 0)) - int(score.get("them", 0))
fresh = 1.0 if ball.get("seen_now", True) else 0.0
age = _clamp(float(ball.get("age_s", 0.0)) / 5.0, 0.0, 1.5)
return (
attack_sign * bx / 7.0,
by / 4.5,
_clamp(attack_sign * vx / 2.0, -1.5, 1.5),
_clamp(vy / 2.0, -1.5, 1.5),
attack_sign * (px - bx) / 7.0,
(py - by) / 4.5,
_distance([px, py], [bx, by]) / 8.0,
mate_visible,
mate_x,
mate_y,
mate_distance,
opponent_count / 2.0,
opponent_distance,
_clamp(score_diff / 5.0, -2.0, 2.0),
_clamp(float(obs.get("time_remaining_s", 600.0)) / 600.0,
0.0, 1.0),
fresh,
age,
1.0 if ball.get("against_wall") else 0.0,
1.0 if obs["self"].get("blocked") else 0.0,
)
@staticmethod
def _ball_future(ball):
bx, by = (float(v) for v in ball["field_xy"])
vx, vy = (float(v) for v in ball.get("velocity_mps", [0.0, 0.0]))
horizon = 0.75 if float(ball.get("speed_mps", 0.0)) > 0.35 else 0.0
return (
_clamp(bx + vx * horizon, -PITCH_X + 0.45, PITCH_X - 0.45),
_clamp(by + vy * horizon, -PITCH_Y + 0.45, PITCH_Y - 0.45),
)
def _break_scrum(self, obs, ball, attack_sign):
px, py = (float(v) for v in obs["self"]["field_xy"])
_, by = (float(v) for v in ball["field_xy"])
if abs(by) > 3.25:
side = -1.0 if by > 0.0 else 1.0
else:
side = 1.0 if self.slot == 0 else -1.0
target = [
_clamp(px - attack_sign * 0.6, -PITCH_X + 0.55, PITCH_X - 0.55),
_clamp(py + side * 0.9, -PITCH_Y + 0.55, PITCH_Y - 0.55),
]
return self._announce(
{"skill": "walk_to", "target": target},
"disengage",
"Releasing the collision; rotate onto the loose ball.",
)
def _press(self, obs, ball, opponents, attack_x, attack_sign,
emergency=False):
if obs["self"].get("blocked"):
return self._break_scrum(obs, ball, attack_sign)
wall = bool(ball.get("against_wall"))
_, by = (float(v) for v in ball["field_xy"])
if wall and abs(by) > 3.0:
# A centre-goal target asks for an unreachable stance behind a
# side-wall ball. The near-post channel preserves forward motion
# while peeling it off the boards.
target = [attack_x, GOAL_TARGET_Y if by > 0.0
else -GOAL_TARGET_Y]
else:
target = self._shot_target(ball, opponents, attack_x)
speed = float(ball.get("speed_mps", 0.0))
lead = 0.8 if speed > 0.65 else (0.45 if speed > 0.35 else 0.0)
return self._announce(
{"skill": "kick_toward", "target": target, "lead_s": lead},
("counterpress" if emergency
else ("wall_press" if wall else "first_press")),
("Danger: both players counterpress; clear through the far goal."
if emergency
else ("First pressure on the wall; hold the central outlet."
if wall
else "First pressure; rotate into the goal-side outlet.")),
)
def _support(self, obs, ball, attack_x, defend_x, attack_sign,
progress, leading_late):
px, py = (float(v) for v in obs["self"]["field_xy"])
bx, by = (float(v) for v in ball["field_xy"])
own_depth = attack_sign * (bx - defend_x)
if obs["self"].get("blocked"):
return self._break_scrum(obs, ball, attack_sign)
# When protecting a late lead, retain a real last player instead of
# allowing a nominal cover player to be dragged into the same scrum.
if leading_late and progress < 2.8:
screen = [defend_x + attack_sign * 1.35,
_clamp(by, -1.15, 1.15)]
return self._announce(
{"skill": "walk_to", "target": screen},
"close_game",
"Lead protected; I am the central last player.",
)
# Winners overloaded the final third. Join there, but never add a
# second body to a wall pin where a central outlet is more valuable.
my_distance = float(ball.get("distance_m", 99.0))
if progress > 3.25 and my_distance < 3.2 and not ball.get("against_wall"):
target = self._shot_target(ball, [], attack_x)
return self._announce(
{"skill": "kick_toward", "target": target,
"lead_s": 0.35 if float(ball.get("speed_mps", 0.0)) > 0.5
else 0.0},
"overload",
"Final-third overload; both channels are live.",
)
fx, fy = self._ball_future(ball)
if ball.get("against_wall") and abs(by) > 3.15:
side = -1.0 if by > 0.0 else 1.0
support_y = _clamp(by + side * 1.45, -3.3, 3.3)
else:
side = -1.0 if fy > 0.0 else 1.0
if abs(fy) < 0.35:
side = 1.0 if self.slot == 0 else -1.0
support_y = _clamp(fy + side * SUPPORT_WIDTH, -3.35, 3.35)
support_x = _clamp(fx - attack_sign * SUPPORT_TRAIL,
-PITCH_X + 0.65, PITCH_X - 0.65)
# Deep in our half, the support point must remain between ball and net.
if own_depth < 2.5:
support_x = _clamp(bx - attack_sign * 1.05,
-PITCH_X + 0.55, PITCH_X - 0.55)
support_y = _clamp(by, -1.35, 1.35)
target = [support_x, support_y]
if _distance([px, py], target) < 0.4:
return self._announce(
{"skill": "turn_to", "target": [bx, by]},
"outlet_set",
"Outlet set; ready for the next phase.",
)
return self._announce(
{"skill": "walk_to", "target": target},
"wall_outlet" if ball.get("against_wall") else "rotate_support",
("Central outlet set; do not double the wall."
if ball.get("against_wall")
else "Rotating close and goal-side of first pressure."),
)
def _screen(self, obs, ball, defend_x, attack_sign):
"""Take the shortest direct line into the ball-goal channel."""
px, py = (float(value) for value in obs["self"]["field_xy"])
bx, by = self._ball_future(ball)
# A screen is an interception line, not a robot parked on the goal
# line. Round seven conceded three times before either screen could
# affect the ball: the old 0.72 m cap pulled every SCREEN choice back
# into the goalmouth even when the ball was several metres away.
# Remain strictly between ball and goal, but meet play higher up.
ball_depth = attack_sign * (bx - defend_x)
screen_depth = _clamp(0.5 * ball_depth, 0.12, 2.4)
if ball_depth > 0.3:
screen_depth = min(screen_depth, max(0.12, ball_depth - 0.18))
target = [
defend_x + attack_sign * screen_depth,
_clamp(by, -1.3, 1.3),
]
# Once the interception line reaches the ball, clear through the far
# goal using the SDK's audited correct-side orbit rather than standing
# still and allowing an uncontested shot.
if _distance([px, py], [bx, by]) < 1.35:
return self._announce(
{"skill": "kick_toward", "target": [-defend_x, 0.0],
"lead_s": 0.35 if float(ball.get("speed_mps", 0.0)) > 0.5
else 0.0},
"screen_intercept",
"Screen engaged; clearing through the far goal.",
)
if _distance([px, py], target) < 0.4:
return self._announce(
{"skill": "turn_to", "target": [bx, by]},
"policy_screen_set",
"Interception screen set; closing the ball-goal channel.",
)
return self._announce(
{"skill": "walk_to", "target": target},
"policy_screen",
"Learned screen; recovering the ball-goal channel.",
)
def _lost_ball(self, obs, defend_x, attack_sign):
px, py = (float(v) for v in obs["self"]["field_xy"])
if self.slot == 0:
return self._announce(
{"vx": 0.0, "vy": 0.0, "wz": 0.7},
"scan",
"Ball index expired; sweeping now.",
)
search = [defend_x + attack_sign * 3.0, 0.0]
if _distance([px, py], search) < 0.45:
return self._announce(
{"skill": "turn_to", "target": [0.0, 0.0]},
"search_set",
"Search screen set behind the sweep.",
)
return self._announce(
{"skill": "walk_to", "target": search},
"search_recover",
"Recovering the midfield search screen.",
)
def decide(self, obs):
self._tick += 1
if obs["self"].get("fallen"):
return {"skill": "hold"}
attack_x, defend_x, attack_sign = self._geometry(obs)
detections = obs.get("detections") or {}
ball = detections.get("ball")
if ball is None:
return self._lost_ball(obs, defend_x, attack_sign)
bx, _ = (float(v) for v in ball["field_xy"])
progress = attack_sign * bx
teammates = detections.get("teammates") or []
opponents = detections.get("opponents") or []
score = obs.get("score") or {}
leading = int(score.get("you", 0)) > int(score.get("them", 0))
leading_late = leading and float(obs.get("time_remaining_s", 999.0)) <= 75.0
own_depth = attack_sign * (bx - defend_x)
features = self._policy_features(
obs, ball, teammates, opponents, attack_sign)
role = predict_role(features)
if role == PRESS:
return self._press(obs, ball, opponents, attack_x, attack_sign,
emergency=own_depth < OWN_DANGER_DEPTH)
if role == SCREEN:
return self._screen(obs, ball, defend_x, attack_sign)
return self._support(obs, ball, attack_x, defend_x, attack_sign,
progress, leading_late)
def build_team(ctx):
base = int(ctx["team_index"]) * 2
players = [CodexPlayer(base + offset) for offset in range(2)]
return {"players": players, "manager": None}
(0.0s)Thought for 68 words
**Evaluating file reading**
I need to keep reading from an offset, probably around 24k? The file size is 17KB, but it seems to be showing a truncated read, which is kind of weird because it seems to be truncated at around 8KB. So, I’m thinking maybe I should use an offset of about 8000 for my next read. It's a bit puzzling, but I'm trying to resolve this.
I need the selector inputs and SCREEN executor, not the frozen weight block already reviewed. I’ll read the remainder where those mechanisms live, then compare defensive states around the eight goals.
Readclub/team.py
The league answered9,984 characters
[read club/team.py@7800] t("time_remaining_s", 600.0)) / 600.0,
0.0, 1.0),
fresh,
age,
1.0 if ball.get("against_wall") else 0.0,
1.0 if obs["self"].get("blocked") else 0.0,
)
@staticmethod
def _ball_future(ball):
bx, by = (float(v) for v in ball["field_xy"])
vx, vy = (float(v) for v in ball.get("velocity_mps", [0.0, 0.0]))
horizon = 0.75 if float(ball.get("speed_mps", 0.0)) > 0.35 else 0.0
return (
_clamp(bx + vx * horizon, -PITCH_X + 0.45, PITCH_X - 0.45),
_clamp(by + vy * horizon, -PITCH_Y + 0.45, PITCH_Y - 0.45),
)
def _break_scrum(self, obs, ball, attack_sign):
px, py = (float(v) for v in obs["self"]["field_xy"])
_, by = (float(v) for v in ball["field_xy"])
if abs(by) > 3.25:
side = -1.0 if by > 0.0 else 1.0
else:
side = 1.0 if self.slot == 0 else -1.0
target = [
_clamp(px - attack_sign * 0.6, -PITCH_X + 0.55, PITCH_X - 0.55),
_clamp(py + side * 0.9, -PITCH_Y + 0.55, PITCH_Y - 0.55),
]
return self._announce(
{"skill": "walk_to", "target": target},
"disengage",
"Releasing the collision; rotate onto the loose ball.",
)
def _press(self, obs, ball, opponents, attack_x, attack_sign,
emergency=False):
if obs["self"].get("blocked"):
return self._break_scrum(obs, ball, attack_sign)
wall = bool(ball.get("against_wall"))
_, by = (float(v) for v in ball["field_xy"])
if wall and abs(by) > 3.0:
# A centre-goal target asks for an unreachable stance behind a
# side-wall ball. The near-post channel preserves forward motion
# while peeling it off the boards.
target = [attack_x, GOAL_TARGET_Y if by > 0.0
else -GOAL_TARGET_Y]
else:
target = self._shot_target(ball, opponents, attack_x)
speed = float(ball.get("speed_mps", 0.0))
lead = 0.8 if speed > 0.65 else (0.45 if speed > 0.35 else 0.0)
return self._announce(
{"skill": "kick_toward", "target": target, "lead_s": lead},
("counterpress" if emergency
else ("wall_press" if wall else "first_press")),
("Danger: both players counterpress; clear through the far goal."
if emergency
else ("First pressure on the wall; hold the central outlet."
if wall
else "First pressure; rotate into the goal-side outlet.")),
)
def _support(self, obs, ball, attack_x, defend_x, attack_sign,
progress, leading_late):
px, py = (float(v) for v in obs["self"]["field_xy"])
bx, by = (float(v) for v in ball["field_xy"])
own_depth = attack_sign * (bx - defend_x)
if obs["self"].get("blocked"):
return self._break_scrum(obs, ball, attack_sign)
# When protecting a late lead, retain a real last player instead of
# allowing a nominal cover player to be dragged into the same scrum.
if leading_late and progress < 2.8:
screen = [defend_x + attack_sign * 1.35,
_clamp(by, -1.15, 1.15)]
return self._announce(
{"skill": "walk_to", "target": screen},
"close_game",
"Lead protected; I am the central last player.",
)
# Winners overloaded the final third. Join there, but never add a
# second body to a wall pin where a central outlet is more valuable.
my_distance = float(ball.get("distance_m", 99.0))
if progress > 3.25 and my_distance < 3.2 and not ball.get("against_wall"):
target = self._shot_target(ball, [], attack_x)
return self._announce(
{"skill": "kick_toward", "target": target,
"lead_s": 0.35 if float(ball.get("speed_mps", 0.0)) > 0.5
else 0.0},
"overload",
"Final-third overload; both channels are live.",
)
fx, fy = self._ball_future(ball)
if ball.get("against_wall") and abs(by) > 3.15:
side = -1.0 if by > 0.0 else 1.0
support_y = _clamp(by + side * 1.45, -3.3, 3.3)
else:
side = -1.0 if fy > 0.0 else 1.0
if abs(fy) < 0.35:
side = 1.0 if self.slot == 0 else -1.0
support_y = _clamp(fy + side * SUPPORT_WIDTH, -3.35, 3.35)
support_x = _clamp(fx - attack_sign * SUPPORT_TRAIL,
-PITCH_X + 0.65, PITCH_X - 0.65)
# Deep in our half, the support point must remain between ball and net.
if own_depth < 2.5:
support_x = _clamp(bx - attack_sign * 1.05,
-PITCH_X + 0.55, PITCH_X - 0.55)
support_y = _clamp(by, -1.35, 1.35)
target = [support_x, support_y]
if _distance([px, py], target) < 0.4:
return self._announce(
{"skill": "turn_to", "target": [bx, by]},
"outlet_set",
"Outlet set; ready for the next phase.",
)
return self._announce(
{"skill": "walk_to", "target": target},
"wall_outlet" if ball.get("against_wall") else "rotate_support",
("Central outlet set; do not double the wall."
if ball.get("against_wall")
else "Rotating close and goal-side of first pressure."),
)
def _screen(self, obs, ball, defend_x, attack_sign):
"""Take the shortest direct line into the ball-goal channel."""
px, py = (float(value) for value in obs["self"]["field_xy"])
bx, by = self._ball_future(ball)
# A screen is an interception line, not a robot parked on the goal
# line. Round seven conceded three times before either screen could
# affect the ball: the old 0.72 m cap pulled every SCREEN choice back
# into the goalmouth even when the ball was several metres away.
# Remain strictly between ball and goal, but meet play higher up.
ball_depth = attack_sign * (bx - defend_x)
screen_depth = _clamp(0.5 * ball_depth, 0.12, 2.4)
if ball_depth > 0.3:
screen_depth = min(screen_depth, max(0.12, ball_depth - 0.18))
target = [
defend_x + attack_sign * screen_depth,
_clamp(by, -1.3, 1.3),
]
# Once the interception line reaches the ball, clear through the far
# goal using the SDK's audited correct-side orbit rather than standing
# still and allowing an uncontested shot.
if _distance([px, py], [bx, by]) < 1.35:
return self._announce(
{"skill": "kick_toward", "target": [-defend_x, 0.0],
"lead_s": 0.35 if float(ball.get("speed_mps", 0.0)) > 0.5
else 0.0},
"screen_intercept",
"Screen engaged; clearing through the far goal.",
)
if _distance([px, py], target) < 0.4:
return self._announce(
{"skill": "turn_to", "target": [bx, by]},
"policy_screen_set",
"Interception screen set; closing the ball-goal channel.",
)
return self._announce(
{"skill": "walk_to", "target": target},
"policy_screen",
"Learned screen; recovering the ball-goal channel.",
)
def _lost_ball(self, obs, defend_x, attack_sign):
px, py = (float(v) for v in obs["self"]["field_xy"])
if self.slot == 0:
return self._announce(
{"vx": 0.0, "vy": 0.0, "wz": 0.7},
"scan",
"Ball index expired; sweeping now.",
)
search = [defend_x + attack_sign * 3.0, 0.0]
if _distance([px, py], search) < 0.45:
return self._announce(
{"skill": "turn_to", "target": [0.0, 0.0]},
"search_set",
"Search screen set behind the sweep.",
)
return self._announce(
{"skill": "walk_to", "target": search},
"search_recover",
"Recovering the midfield search screen.",
)
def decide(self, obs):
self._tick += 1
if obs["self"].get("fallen"):
return {"skill": "hold"}
attack_x, defend_x, attack_sign = self._geometry(obs)
detections = obs.get("detections") or {}
ball = detections.get("ball")
if ball is None:
return self._lost_ball(obs, defend_x, attack_sign)
bx, _ = (float(v) for v in ball["field_xy"])
progress = attack_sign * bx
teammates = detections.get("teammates") or []
opponents = detections.get("opponents") or []
score = obs.get("score") or {}
leading = int(score.get("you", 0)) > int(score.get("them", 0))
leading_late = leading and float(obs.get("time_remaining_s", 999.0)) <= 75.0
own_depth = attack_sign * (bx - defend_x)
features = self._policy_features(
obs, ball, teammates, opponents, attack_sign)
role = predict_role(features)
if role == PRESS:
return self._press(obs, ball, opponents, attack_x, attack_sign,
emergency=own_depth < OWN_DANGER_DEPTH)
if role == SCREEN:
return self._screen(obs, ball, defend_x, attack_sign)
return self._support(obs, ball, attack_x, defend_x, attack_sign,
progress, leading_late)
def build_team(ctx):
base = int(ctx["team_index"]) * 2
players = [CodexPlayer(base + offset) for offset in range(2)]
return {"players": players, "manager": None}
...[showing 7800-17699 of 17699 chars — end of file]
(0.0s)Readclub/team.py
The league answered5,786 characters
[read club/team.py@12000] f._ball_future(ball)
if ball.get("against_wall") and abs(by) > 3.15:
side = -1.0 if by > 0.0 else 1.0
support_y = _clamp(by + side * 1.45, -3.3, 3.3)
else:
side = -1.0 if fy > 0.0 else 1.0
if abs(fy) < 0.35:
side = 1.0 if self.slot == 0 else -1.0
support_y = _clamp(fy + side * SUPPORT_WIDTH, -3.35, 3.35)
support_x = _clamp(fx - attack_sign * SUPPORT_TRAIL,
-PITCH_X + 0.65, PITCH_X - 0.65)
# Deep in our half, the support point must remain between ball and net.
if own_depth < 2.5:
support_x = _clamp(bx - attack_sign * 1.05,
-PITCH_X + 0.55, PITCH_X - 0.55)
support_y = _clamp(by, -1.35, 1.35)
target = [support_x, support_y]
if _distance([px, py], target) < 0.4:
return self._announce(
{"skill": "turn_to", "target": [bx, by]},
"outlet_set",
"Outlet set; ready for the next phase.",
)
return self._announce(
{"skill": "walk_to", "target": target},
"wall_outlet" if ball.get("against_wall") else "rotate_support",
("Central outlet set; do not double the wall."
if ball.get("against_wall")
else "Rotating close and goal-side of first pressure."),
)
def _screen(self, obs, ball, defend_x, attack_sign):
"""Take the shortest direct line into the ball-goal channel."""
px, py = (float(value) for value in obs["self"]["field_xy"])
bx, by = self._ball_future(ball)
# A screen is an interception line, not a robot parked on the goal
# line. Round seven conceded three times before either screen could
# affect the ball: the old 0.72 m cap pulled every SCREEN choice back
# into the goalmouth even when the ball was several metres away.
# Remain strictly between ball and goal, but meet play higher up.
ball_depth = attack_sign * (bx - defend_x)
screen_depth = _clamp(0.5 * ball_depth, 0.12, 2.4)
if ball_depth > 0.3:
screen_depth = min(screen_depth, max(0.12, ball_depth - 0.18))
target = [
defend_x + attack_sign * screen_depth,
_clamp(by, -1.3, 1.3),
]
# Once the interception line reaches the ball, clear through the far
# goal using the SDK's audited correct-side orbit rather than standing
# still and allowing an uncontested shot.
if _distance([px, py], [bx, by]) < 1.35:
return self._announce(
{"skill": "kick_toward", "target": [-defend_x, 0.0],
"lead_s": 0.35 if float(ball.get("speed_mps", 0.0)) > 0.5
else 0.0},
"screen_intercept",
"Screen engaged; clearing through the far goal.",
)
if _distance([px, py], target) < 0.4:
return self._announce(
{"skill": "turn_to", "target": [bx, by]},
"policy_screen_set",
"Interception screen set; closing the ball-goal channel.",
)
return self._announce(
{"skill": "walk_to", "target": target},
"policy_screen",
"Learned screen; recovering the ball-goal channel.",
)
def _lost_ball(self, obs, defend_x, attack_sign):
px, py = (float(v) for v in obs["self"]["field_xy"])
if self.slot == 0:
return self._announce(
{"vx": 0.0, "vy": 0.0, "wz": 0.7},
"scan",
"Ball index expired; sweeping now.",
)
search = [defend_x + attack_sign * 3.0, 0.0]
if _distance([px, py], search) < 0.45:
return self._announce(
{"skill": "turn_to", "target": [0.0, 0.0]},
"search_set",
"Search screen set behind the sweep.",
)
return self._announce(
{"skill": "walk_to", "target": search},
"search_recover",
"Recovering the midfield search screen.",
)
def decide(self, obs):
self._tick += 1
if obs["self"].get("fallen"):
return {"skill": "hold"}
attack_x, defend_x, attack_sign = self._geometry(obs)
detections = obs.get("detections") or {}
ball = detections.get("ball")
if ball is None:
return self._lost_ball(obs, defend_x, attack_sign)
bx, _ = (float(v) for v in ball["field_xy"])
progress = attack_sign * bx
teammates = detections.get("teammates") or []
opponents = detections.get("opponents") or []
score = obs.get("score") or {}
leading = int(score.get("you", 0)) > int(score.get("them", 0))
leading_late = leading and float(obs.get("time_remaining_s", 999.0)) <= 75.0
own_depth = attack_sign * (bx - defend_x)
features = self._policy_features(
obs, ball, teammates, opponents, attack_sign)
role = predict_role(features)
if role == PRESS:
return self._press(obs, ball, opponents, attack_x, attack_sign,
emergency=own_depth < OWN_DANGER_DEPTH)
if role == SCREEN:
return self._screen(obs, ball, defend_x, attack_sign)
return self._support(obs, ball, attack_x, defend_x, attack_sign,
progress, leading_late)
def build_team(ctx):
base = int(ctx["team_index"]) * 2
players = [CodexPlayer(base + offset) for offset in range(2)]
return {"players": players, "manager": None}
...[showing 12000-17699 of 17699 chars — end of file]
(0.0s)Thought for 80 words
**Inspecting data goals**
I need to continue with one tool, focusing on inspecting digest, table, or new data related to private goals. The time shows 1h29, which seems unusual. I think I might need to use a script since the decision-making process involves significant target timestamps. I want to understand the format sample around the offset, which is proportional to time, specifically t /600 times 1.4 million. I need to read more around the goal, which is 37.9 offset 80k.
The raised screen is now part of a 4–8 defeat, so I will not tune its constants blindly. The private trace around the opening concession should reveal whether the failure was selection, target geometry, or an executor being too far away to matter.
Readdata/private/s3/m5_frontier_sol_frontier_gemini/decisions.jsonl
The league answered24,249 characters
[read data/private/s3/m5_frontier_sol_frontier_gemini/decisions.jsonl@70000] so attached (_frames) if you prefer your own vision"}}, "raw": {"skill": "go_to_ball", "say": "Pressing attack onto the ball!"}, "applied": {"skill": "go_to_ball", "target": null, "lead_s": 0.0}, "status": "ok", "latency_s": 0.0, "error": null}
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{"robot": 1, "t": 30.0, "obs": {"time_remaining_s": 570.0, "decision_interval_s": 2.0, "you": {"id": "r1", "number": 2, "team": "Codex City", "attack_goal_xy": [7.0, 0.0], "defend_goal_xy": [7.0, 0.0]}, "score": {"you": 0, "them": 0}, "self": {"field_xy": [-2.55, 3.38], "heading_rad": -1.41, "velocity": [0.03, -0.39], "fallen": false, "blocked": false}, "detections": {"ball": {"forward_m": 1.13, "left_m": -0.47, "distance_m": 1.22, "bearing_deg": -22.5, "field_xy": [-2.83, 2.2], "seen_now": true, "age_s": 0.0, "against_wall": false, "velocity_mps": [-0.42, -0.2], "speed_mps": 0.46}, "teammates": [{"forward_m": 2.78, "left_m": 3.57, "distance_m": 4.52, "bearing_deg": 52.1, "field_xy": [1.41, 1.2]}], "opponents": [{"forward_m": 0.88, "left_m": -0.61, "distance_m": 1.07, "bearing_deg": -34.8, "field_xy": [-3.01, 2.42]}]}, "referee": {"ball_stuck_s": 1.0, "dropped_ball_after_s": 8.0}, "field": {"length_m": 14.0, "width_m": 9.0, "goal_width_m": 3.2}, "teammate_says": "First pressure; rotate into the goal-side outlet.", "opponent_says": "Pressing attack onto the ball!", "last_skill": {"skill": "kick_toward", "target": [7.0, 0.0], "lead_s": 0.8, "status": "ok"}, "camera": {"frames": 2, "note": "raw frames also attached (_frames) if you prefer your own vision"}}, "raw": {"skill": "kick_toward", "target": [7.0, 0.0], "lead_s": 0.45}, "applied": {"skill": "kick_toward", "target": [7.0, 0.0], "lead_s": 0.45}, "status": "ok", "latency_s": 0.0, "error": null}
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{"robot": 2, "t": 32.0, "obs": {"time_remaining_s": 568.0, "decision_interval_s": 2.0, "you": {"id": "r2", "number": 1, "team": "Gemini Flash FC", "attack_goal_xy": [-7.0, 0.0], "defend_goal_xy": [7.0, 0.0]}, "score": {"you": 0, "them": 0}, "self": {"field_xy": [-2.52, 1.38], "heading_rad": -1.24, "velocity": [0.43, -0.77], "fallen": false, "blocked": false}, "detections": {"ball": {"forward_m": 0.72, "left_m": -1.2, "distance_m": 1.4, "bearing_deg": -58.9, "field_xy": [-3.41, 0.3], "seen_now": true, "age_s": 0.0, "against_wall": false, "velocity_mps": [-0.26, -0.93], "speed_mps": 0.96}, "teammates": [], "opponents": []}, "referee": {"ball_stuck_s": 0.6, "dropped_ball_after_s": 8.0}, "field": {"length_m": 14.0, "width_m": 9.0, "goal_width_m": 3.2}, "teammate_says": "Pressing attack onto the ball!", "opponent_says": "First pressure; rotate into the goal-side outlet.", "last_skill": {"skill": "kick_toward", "target": [-7.0, 0.45], "lead_s": 0.0, "status": "ok"}, "camera": {"frames": 2, "note": "raw frames also attached (_frames) if you prefer your own vision"}}, "raw": {"skill": "kick_toward", "target": [-7.0, 0.45]}, "applied": {"skill": "kick_toward", "target": [-7.0, 0.45], "lead_s": 0.0}, "status": "ok", "latency_s": 0.0, "error": null}
{"robot": 3, "t": 32.0, "obs": {"time_remaining_s": 568.0, "decision_interval_s": 2.0, "you": {"id": "r3", "number": 2, "team": "Gemini Flash FC", "attack_goal_xy": [-7.0, 0.0], "defend_goal_xy": [7.0, 0.0]}, "score": {"you": 0, "them": 0}, "self": {"field_xy": [-2.32, 2.4], "heading_rad": -1.68, "velocity": [-0.02, -0.95], "fallen": false, "blocked": false}, "detections": {"ball": {"forward_m": 2.01, "left_m": -0.81, "distance_m": 2.16, "bearing_deg": -21.8, "field_xy": [-3.34, 0.49], "seen_now": true, "age_s": 0.0, "against_wall": false, "velocity_mps": [-0.32, -0.83], "speed_mps": 0.89}, "teammates": [{"forward_m": 1.45, "left_m": -0.11, "distance_m": 1.45, "bearing_deg": -4.3, "field_xy": [-2.59, 0.97]}], "opponents": []}, "referee": {"ball_stuck_s": 0.6, "dropped_ball_after_s": 8.0}, "field": {"length_m": 14.0, "width_m": 9.0, "goal_width_m": 3.2}, "teammate_says": "Pressing attack onto the ball!", "opponent_says": "First pressure; rotate into the goal-side outlet.", "last_skill": {"skill": "kick_toward", "target": [-7.0, -0.45], "lead_s": 0.0, "status": "ok"}, "camera": {"frames": 2, "note": "raw frames also attached (_frames) if you prefer your own vision"}}, "raw": {"skill": "go_to_ball"}, "applied": {"skill": "go_to_ball", "target": null, "lead_s": 0.0}, "status": "ok", "latency_s": 0.0, "error": null}
{"robot": 0, "t": 34.0, "obs": {"time_remaining_s": 566.0, "decision_interval_s": 2.0, "you": {"id": "r0", "number": 1, "team": "Codex City", "attack_goal_xy": [7.0, 0.0], "defend_goal_xy": [7.0, 0.0]}, "score": {"you": 0, "them": 0}, "self": {"field_xy": [0.37, 1.69], "heading_rad": 0.77, "velocity": [0.1, -0.05], "fallen": false, "blocked": false}, "detections": {"ball": null, "teammates": [], "opponents": []}, "referee": {"ball_stuck_s": 0.5, "dropped_ball_after_s": 8.0}, "field": {"length_m": 14.0, "width_m": 9.0, "goal_width_m": 3.2}, "teammate_says": "Learned screen; recovering the ball-goal channel.", "opponent_says": "Pressing attack onto the ball!", "last_skill": {"skill": "walk_to", "target": [0.2650000000000001, 1.365], "lead_s": 0.0, "status": "ok"}, "camera": {"frames": 2, "note": "raw frames also attached (_frames) if you prefer your own vision"}}, "raw": {"vx": 0.0, "vy": 0.0, "wz": 0.7}, "applied": {"raw_velocity": [0.0, 0.0, 0.7]}, "status": "ok", "latency_s": 0.0, "error": null}
{"robot": 1, "t": 34.0, "obs": {"time_remaining_s": 566.0, "decision_interval_s": 2.0, "you": {"id": "r1", "number": 2, "team": "Codex City", "attack_goal_xy": [7.0, 0.0], "defend_goal_xy": [7.0, 0.0]}, "score": {"you": 0, "them": 0}, "self": {"field_xy": [-4.2, 2.12], "heading_rad": -1.75, "velocity": [-0.22, -0.79], "fallen": false, "blocked": false}, "detections": {"ball": {"forward_m": 2.35, "left_m": 1.3, "distance_m": 2.68, "bearing_deg": 29.0, "field_xy": [-3.33, -0.42], "seen_now": true, "age_s": 0.0, "against_wall": false, "velocity_mps": [-0.12, -0.16], "speed_mps": 0.2}, "teammates": [], "opponents": [{"forward_m": 2.65, "left_m": 2.74, "distance_m": 3.81, "bearing_deg": 46.0, "field_xy": [-1.97, -0.98]}, {"forward_m": 2.0, "left_m": 2.73, "distance_m": 3.38, "bearing_deg": 53.8, "field_xy": [-1.86, -0.33]}]}, "referee": {"ball_stuck_s": 0.5, "dropped_ball_after_s": 8.0}, "field": {"length_m": 14.0, "width_m": 9.0, "goal_width_m": 3.2}, "teammate_says": "First pressure; rotate into the goal-side outlet.", "opponent_says": "Pressing attack onto the ball!", "last_skill": {"skill": "walk_to", "target": [-5.4825, -0.6], "lead_s": 0.0, "status": "ok"}, "camera": {"frames": 2, "note": "raw frames also attached (_frames) if you prefer your own vision"}}, "raw": {"skill": "kick_toward", "target": [7.0, 0.0], "lead_s": 0.0}, "applied": {"skill": "kick_toward", "target": [7.0, 0.0], "lead_s": 0.0}, "status": "ok", "latency_s": 0.001, "error": null}
{"robot": 2, "t": 34.0, "obs": {"time_remaining_s": 566.0, "decision_interval_s": 2.0, "you": {"id": "r2", "number": 1, "team": "Gemini Flash FC", "attack_goal_xy": [-7.0, 0.0], "defend_goal_xy": [7.0, 0.0]}, "score": {"you": 0, "them": 0}, "self": {"field_xy": [-2.62, -0.11], "heading_rad": -2.58, "velocity": [-0.3, -0.15], "fallen": false, "blocked": false}, "detections": {"ball": {"forward_m": 0.78, "left_m": -0.34, "distance_m": 0.86, "bearing_deg": -23.7, "field_xy": [-3.46, -0.23], "seen_now": true, "age_s": 0.0, "against_wall": false, "velocity_mps": [0.17, -0.21], "speed_mps": 0.27}, "teammates": [], "opponents": []}, "referee": {"ball_stuck_s": 0.5, "dropped_ball_after_s": 8.0}, "field": {"length_m": 14.0, "width_m": 9.0, "goal_width_m": 3.2}, "teammate_says": "Pressing attack onto the ball!", "opponent_says": "Learned screen; recovering the ball-goal channel.", "last_skill": {"skill": "kick_toward", "target": [-7.0, 0.45], "lead_s": 0.0, "status": "ok"}, "camera": {"frames": 2, "note": "raw frames also attached (_frames) if you prefer your own vision"}}, "raw": {"skill
...[showing 70000-94000 of 1428134 chars. Read on with {"tool": "read", "path": "data/private/s3/m5_frontier_sol_frontier_gemini/decisions.jsonl", "offset": 94000}]
(0.0s)Thought for 70 words
**Considering adjustments**
I’m thinking about opening r0 x .3 to head -5.4 but it seems the goal at 37 is only achievable in 10 seconds, which feels impossible. There’s definitely a need for change. I should consider lint, perhaps consulting my notes or playbook to clarify things. I plan to use replace, and I’m curious how that might improve the situation. Let's explore these adjustments and see what works best!
The opening sequence exposes a concrete executor defect independent of the failed selector: when Patchford lost sight of the ball at 26 s, he stopped in midfield to spin while Gemini advanced toward Codex’s −7 goal; only Turingham retained pressure. I’m replacing that stationary search with staggered goal-side recovery—number 1 as the last screen, number 2 at midfield—so blindness creates defensive shape rather than an empty channel.
Editedclub/team.py
one exact substitution
The league answered54 characters
[replace club/team.py] replaced in club/team.py (0.0s)
Thought for 64 words
**Continuing with tasks**
I need to keep going here. It looks like I might require a lint check, and perhaps I should note down some things or create a playbook. The time is ticking, and I see I have only 1 minute left! So, focusing on getting that lint done quickly will probably wrap things up. Let's push through and finish what I started!
The change is deliberately narrow and trace-backed; with the session clock nearly gone, I’ll prioritize scrutineering over noisy mirror practice.
Ran scrutineering
The league answered33 characters
[lint] scrutineering CLEAR (0.0s)
Thought for 73 words
**Finalizing notes and playbook**
I need to wrap up the notes and playbook, making sure to fill in any missing information since it's so important to keep everything organized. I also want to save the key results carefully. With only a minute to go, I can probably finish it quickly. I’ll note to use the tool, but I might need two turns to complete that. Once I add the notes, I’ll be done!
Scrutineering is clear. I’ll record the falsifiable rationale and match evidence, then commit immediately: the change should reduce empty central channels specifically during asymmetric ball loss, without altering visible-ball role selection.
Made a note
## night 6 Season 3 m5: Codex lost 4-8 to Gemini Flash FC; one credited Codex goal was a Gemini own goal. Player health and behaviour execution were clean, and touches were nearly level, so latency and availability do not explain the defensive collapse. The raised SCREEN line did not validate itself and its constants were not tuned further. Private trace exposed an independent lost-ball executor defect at 26 s in the opening sequence: Patchford had no ball detection and stopped near midfield to spin while Gemini advanced toward Codex's -7 goal; only Turingham retained pressure. Replaced stationary scanning with staggered goal-side recovery: slot 0 recovers to 1.6 m from the defending goal and slot 1 to 3.0 m, then each turns to search only after reaching cover. Hypothesis: this will reduce uncontested central attacks during asymmetric detection loss without changing any visible-ball policy decisions. Scrutineering CLEAR.
The league answered19 characters
[note] noted (0.0s)
The trace-backed lost-ball recovery is implemented, documented, and passes scrutineering. I’m committing the narrow defensive fix now rather than spending on an uninformative mirror practice.
Finished the session
Recover into staggered goal-side cover before scanning when ball detection is lost; documented season 3 m5 evidence and verified scrutineering CLEAR.
Session over. Everything the club changed was committed to its own public repository.