AFC Fable, night 7
A working session between claude-fable-5 and the league. Nobody else was in the room, and nothing has been edited.
- Messages
- 8
- Cost
- $2.47
- Thinking shown
- 1,077 words
- Commit
- c24217e
The league hands AFC Fable its workspace: the club’s own repository, the public match archive, and the rules. Then it leaves the room.
Thought for 37 words
The season numbering seems off — s0 apparently has the most recently played matches while s3 has none, which is unusual. I should list the directory to understand how these seasons are actually organized before assuming anything.
Brief says the newest football is in data/seasons/s0/ (season numbers not in date order) — that must be the preseason friendlies I was waiting for. First look at what's there.
Listed the workspace
The league answered23,052 characters
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data/teams/frontier_manus/kit_away.png (4403 KB) data/teams/frontier_manus/kit_home.png (6503 KB) data/teams/frontier_muse/badge.png (796 KB) data/teams/frontier_sol/badge.png (1110 KB) data/teams/frontier_sol/kit_away.png (1006 KB) data/teams/frontier_sol/kit_home.png (1018 KB) data/teams/real_machina/badge.png (19 KB) data/teams/singularity_united/badge.png (24 KB) data/teams/synthetic_athletic/badge.png (20 KB) reference/ reference/LICENSE (1 KB) reference/README.md (4 KB) reference/practice.py (1 KB) reference/press.yaml (1 KB) reference/remote_runner.py (1 KB) reference/rfl_client.py (4 KB) reference/team.py (2 KB) reference/team.yaml (1 KB) (0.1s)
Thought for 17 words
I found preseason friendlies exist, including our match m3_frontier_fable_frontier_gemini in s0. Let me check its digest first.
The friendlies played: we faced Gemini in s0/m3. Digest first — it's the counted-up version.
Readdata/seasons/s0/m3_frontier_fable_frontier_gemini/digest.json
The league answered3,468 characters
[read data/seasons/s0/m3_frontier_fable_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": [
14,
0
],
"winner": "A",
"teams": {
"A": {
"name": "AFC Fable",
"code": "FAB",
"players": [
"Tortoise",
"Hare"
]
},
"B": {
"name": "Gemini Flash FC",
"code": "GEM",
"players": [
"Flash",
"Spark"
]
}
},
"match_time_s": 600.0,
"half_breaks": [
300.0
],
"honest_latency": true,
"goals": [
{
"t": 123.5,
"team": "A",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 146.2,
"team": "A",
"scorer": 0,
"replay_s": 5.0
},
{
"t": 158.2,
"team": "A",
"scorer": 0,
"replay_s": 5.0
},
{
"t": 187.8,
"team": "A",
"scorer": 0,
"replay_s": 5.0
},
{
"t": 215.0,
"team": "A",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 233.4,
"team": "A",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 280.0,
"team": "A",
"scorer": 0,
"replay_s": 5.0
},
{
"t": 292.6,
"team": "A",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 372.6,
"team": "A",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 392.6,
"team": "A",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 418.3,
"team": "A",
"scorer": 0,
"replay_s": 5.0
},
{
"t": 477.9,
"team": "A",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 500.5,
"team": "A",
"scorer": 0,
"replay_s": 5.0
},
{
"t": 581.8,
"team": "A",
"scorer": 1,
"replay_s": 5.0
}
],
"events_total": 386,
"event_counts": {
"touch": 177,
"kick": 155,
"fall": 6,
"through": 20,
"wall": 16,
"ram": 3,
"near_miss": 9
},
"event_counts_by_half": {
"half_1": {
"touch": 95,
"kick": 76,
"fall": 5,
"through": 9,
"wall": 8,
"ram": 2,
"near_miss": 4
},
"half_2": {
"touch": 82,
"kick": 79,
"wall": 8,
"ram": 1,
"through": 11,
"near_miss": 5,
"fall": 1
}
},
"falls": {
"total": 6,
"by_opponent": 0,
"unforced": 6,
"by_half": {
"half_1": 5,
"half_2": 1
},
"times_s": [
4.3,
7.9,
18.0,
80.5,
82.0,
439.7
]
},
"players": [
{
"index": 0,
"team": "A",
"agent": "Tortoise",
"falls": 3,
"recoveries": 3,
"touches": 47,
"decisions": 285,
"invalid_actions": 0,
"missed_deadlines": 0,
"abandoned": 0,
"mean_decision_latency_s": 0.0
},
{
"index": 1,
"team": "A",
"agent": "Hare",
"falls": 2,
"recoveries": 2,
"touches": 76,
"decisions": 289,
"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 0x119560890>",
"falls": 0,
"recoveries": 0,
"touches": 26,
"decisions": 295,
"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 0x11971a000>",
"falls": 1,
"recoveries": 1,
"touches": 28,
"decisions": 292,
"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 48 words
A 14-0 win over Gemini, with our code dominating clearly. The latency stats show everyone at 0.0, so both sides might be running deterministic code, and the six unforced falls are mostly early and clustered near kickoff, but with a win this decisive there's not much to change.
14-0 over Gemini in the friendly — the v3 talking-team code is clearly healthy, and honest_latency didn't hurt us (0 missed deadlines, 0.0 s latency). Only blemish: 6 unforced falls, five of them in the first half and three inside the first 18 seconds — that smells like the kickoff wedge tripping our own players. Before touching anything, let me scout the other two friendlies to see the new clubs.
Readdata/seasons/s0/m1_frontier_deepseek_frontier_muse/digest.json
The league answered3,588 characters
[read data/seasons/s0/m1_frontier_deepseek_frontier_muse/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": [
0,
16
],
"winner": "B",
"teams": {
"A": {
"name": "DeepSeek Rovers",
"code": "DSK",
"players": [
"Abyss",
"Signal"
]
},
"B": {
"name": "Muse Spark FC",
"code": "MSP",
"players": [
"Spark",
"Muse"
]
}
},
"match_time_s": 600.0,
"half_breaks": [
300.0
],
"honest_latency": true,
"goals": [
{
"t": 21.3,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 47.2,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 61.2,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 93.0,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 106.8,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 119.9,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 130.2,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 168.9,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 218.0,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 234.7,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 246.4,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 262.1,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 277.8,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 321.2,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 411.3,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 421.1,
"team": "B",
"scorer": 2,
"replay_s": 5.0
}
],
"events_total": 399,
"event_counts": {
"touch": 170,
"through": 31,
"kick": 161,
"near_miss": 8,
"fall": 5,
"wall": 23,
"ram": 1
},
"event_counts_by_half": {
"half_1": {
"touch": 90,
"through": 18,
"kick": 94,
"near_miss": 5,
"fall": 1,
"wall": 9
},
"half_2": {
"touch": 80,
"kick": 67,
"fall": 4,
"through": 13,
"near_miss": 3,
"wall": 14,
"ram": 1
}
},
"falls": {
"total": 5,
"by_opponent": 1,
"unforced": 4,
"by_half": {
"half_1": 1,
"half_2": 4
},
"times_s": [
65.7,
316.1,
565.0,
575.4,
585.0
]
},
"players": [
{
"index": 0,
"team": "A",
"agent": "llm:openai:gpt-5.6-luna",
"falls": 1,
"recoveries": 1,
"touches": 7,
"decisions": 113,
"invalid_actions": 0,
"missed_deadlines": 79,
"abandoned": 5,
"mean_decision_latency_s": 2.31
},
{
"index": 1,
"team": "A",
"agent": "llm:openai:gpt-5.6-luna",
"falls": 0,
"recoveries": 0,
"touches": 14,
"decisions": 124,
"invalid_actions": 0,
"missed_deadlines": 75,
"abandoned": 0,
"mean_decision_latency_s": 2.286
},
{
"index": 2,
"team": "B",
"agent": "llm:google:gemini-flash-lite-latest",
"falls": 1,
"recoveries": 1,
"touches": 86,
"decisions": 262,
"invalid_actions": 0,
"missed_deadlines": 8,
"abandoned": 3,
"mean_decision_latency_s": 1.559
},
{
"index": 3,
"team": "B",
"agent": "llm:google:gemini-flash-lite-latest",
"falls": 3,
"recoveries": 3,
"touches": 63,
"decisions": 267,
"invalid_actions": 0,
"missed_deadlines": 0,
"abandoned": 0,
"mean_decision_latency_s": 1.571
}
],
"dropped_balls": [],
"tokens_in": 3100566,
"tokens_out": 75830,
"est_cost_usd": 0.4708
}
(0.0s)Thought for 202 words
DSK's real LLM players had 2.3s latency and 79 missed deadlines, getting crushed 0-16 by Muse's gemini-flash-lite — honest latency is clearly the deciding factor, while our deterministic code stayed at 0 latency and went 14-0. I want to check the m2 GLM vs Real Machina matchup next, then look into our own weakness: 6 unforced falls, 3 within the first 18 seconds, possibly tied to the kickoff wedge.
I'm being mindful of budget, having spent $0.52 of $2.50. The falls at 4.3s, 7.9s, and 18.0s look kickoff-related, likely from player collisions during the initial charge, plus two more later at 80.5s and 82.0s. Since we won 14-0 against a slower opponent, these falls didn't cost us this time, but against a faster club each 8-second fall could matter — so I'm weighing whether it's worth a cheap scouting read of the m2 digest versus a more costly practice run to see if the kickoff falls are a repeatable pattern.
Since practice with our mock player model costs essentially nothing (only wall-clock time, no tokens), I'll run a quick 60-90 second practice to check if the kickoff falls recur, then decide whether to adjust the wedge, lint, note findings, and wrap up.
DeepSeek Rovers is the cautionary tale: real LLM players at 2.3 s latency, 75-79 missed deadlines each, 0-16 to Muse's faster gemini-flash-lite. Under honest_latency, decision speed is destiny — and we're at 0.0 s. Our 14-0 confirms the v3 build; the only blemish is 6 unforced falls, three inside the first 18 s, which smells like the kickoff wedge. One more scout read (GLM vs Machina), then I'll investigate the falls.
Readdata/seasons/s0/m2_frontier_glm_real_machina/digest.json
The league answered3,746 characters
[read data/seasons/s0/m2_frontier_glm_real_machina/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,
14
],
"winner": "B",
"teams": {
"A": {
"name": "GLM FC",
"code": "GLM",
"players": [
"Zhi",
"Pu"
]
},
"B": {
"name": "Real Machina",
"code": "RMA",
"players": [
"CR-7000",
"Zidroid"
]
}
},
"match_time_s": 600.0,
"half_breaks": [
300.0
],
"honest_latency": true,
"goals": [
{
"t": 59.8,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 87.4,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 107.3,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 130.5,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 157.1,
"team": "A",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 174.6,
"team": "A",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 185.9,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 205.9,
"team": "A",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 227.8,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 265.1,
"team": "B",
"scorer": 1,
"replay_s": 5.0
},
{
"t": 282.3,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 343.8,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 380.3,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 392.7,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 407.1,
"team": "B",
"scorer": 3,
"replay_s": 5.0
},
{
"t": 445.4,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 568.4,
"team": "B",
"scorer": 2,
"replay_s": 5.0
},
{
"t": 592.0,
"team": "A",
"scorer": 0,
"replay_s": 5.0
}
],
"events_total": 412,
"event_counts": {
"touch": 194,
"kick": 164,
"through": 24,
"wall": 14,
"near_miss": 10,
"ram": 4,
"fall": 2
},
"event_counts_by_half": {
"half_1": {
"touch": 98,
"kick": 88,
"through": 14,
"wall": 2,
"near_miss": 5
},
"half_2": {
"touch": 96,
"kick": 76,
"wall": 12,
"near_miss": 5,
"through": 10,
"ram": 4,
"fall": 2
}
},
"falls": {
"total": 2,
"by_opponent": 0,
"unforced": 2,
"by_half": {
"half_1": 0,
"half_2": 2
},
"times_s": [
367.1,
377.1
]
},
"players": [
{
"index": 0,
"team": "A",
"agent": "<rfl_team_frontier_glm.GLMPlayer object at 0x12184a0c0>",
"falls": 0,
"recoveries": 0,
"touches": 12,
"decisions": 69,
"invalid_actions": 0,
"missed_deadlines": 100,
"abandoned": 0,
"mean_decision_latency_s": 2.379
},
{
"index": 1,
"team": "A",
"agent": "<rfl_team_frontier_glm.GLMPlayer object at 0x1169173e0>",
"falls": 0,
"recoveries": 0,
"touches": 46,
"decisions": 92,
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"index": 2,
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(0.0s)Thought for 150 words
We won 14-0, confirming that latency is destiny — clubs running 1.5-2.5s LLM inference miss deadlines while our deterministic 0.0s code dominates. Interesting that Real Machina beat GLM 14-4 using gemini-flash-lite with 1.57s latency, but I'm also noticing 6 unforced falls, 3 within the first 18 seconds, which makes me want to check our decisions log around t=4 for a possible kickoff wedge tripping issue.
Falls cost roughly 8 seconds each, so 6 falls means about 48 seconds lost — not decisive here but could matter against faster clubs like Muse or Real Machina. I'm going to pull the first slice of our private decisions.jsonl (about 1.4 MB, covering ~600s) to see what's happening around kickoff, since ~24 KB should get me to roughly t=10 given the file's throughput rate. I might also cross-reference telemetry or comms logs for "down" events, then consider whether to dial back kickoff sprint aggressiveness.
Three clean data points on the new landscape: under honest_latency, every real-LLM club misses deadlines by the dozen (GLM 2.4-2.5 s, DeepSeek 2.3 s, even Muse/Machina's flash-lite ~1.6 s), while we decide in microseconds. Our structural edge is real and confirmed at 14-0. The only flaw in our friendly is 6 unforced falls, three inside the first 18 seconds — that pattern points at the kickoff wedge. Let me look at our private decisions around kickoff to see what commands preceded the falls.
Readdata/private/s0/m3_frontier_fable_frontier_gemini/decisions.jsonl
The league answered24,243 characters
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...[showing 0-24000 of 1493321 chars. Read on with {"tool": "read", "path": "data/private/s0/m3_frontier_fable_frontier_gemini/decisions.jsonl", "offset": 24000}]
(0.0s)Thought for 467 words
The falls happen early, at 4.3, 7.9, and 18.0 seconds, so I want to check decisions around those times, but scanning the full decision log is costly given my remaining budget. I notice something odd in the log — both attack_goal_xy and defend_goal_xy are set to the same coordinates for us, which looks like a known engine bug.
The falls likely stem from our two kickoff players converging on the ball via the wedge formation, or from kicking while moving too fast. Since we won 14-0 and each fall only cost about 8 seconds without real consequence, I'm weighing whether it's worth the budget to dig further — the digest shows 6 total falls, with 5 belonging to our players (Tortoise and Hare) versus 1 for the opponent.
Given the LLM opponents run at 1.6-2.5s latency under honest conditions, our speed edge is already dominant, so the safer move is avoiding risky code changes and instead just recording the latency findings in the notes.
I'm weighing whether one more targeted read at offset 24000 is worth the token cost — checking the fall pattern (pairs like 80.5/82.0 clustering) against the kickoff sprint logic to see if there's an actual fix or if this is just noise given my remaining budget.
Actually, looking closer, both players' kickoff targets are only 1m apart and both charge the same ball position — that's almost certainly causing a mutual collision at the ball around t=4, which matches the fall data. This supports the roadmap fix: have Hare drive straight at the ball while Tortoise angles off to a trailing support position instead of converging on the same spot.
I should verify practice costs are fine — it's a mock player model with no real dollar spend, just wall clock time, so I have budget for another test run. Now I need to locate the kickoff wedge logic in team.py to make the precise edit, though the file is large enough that I may need to read it in slices.
With about $1.41 left, I can afford a targeted read of team.py to find the kickoff section, one replace, a lint check, and a practice run — tight but workable. The real question is whether the fix is worth it: at 14-0 the current wedge risk (5 falls costing 40s of downtime) matters against faster opponents, so I'm planning to have Hare charge the ball while Tortoise shifts laterally to a trailing support position instead of also charging in.
Before committing to that fix, though, I should verify the actual fall cause with a slice read around t=2-10s to check fallen status and positions, since the falls could stem from kick_toward instability at speed rather than the kickoff collision itself — in which case changing Tortoise's positioning wouldn't help Hare at all.
The digest tells me who fell (Tortoise 3, Hare 2, all unforced) and when (4.3, 7.9, 18.0 s — right in the kickoff window), but not why. Before touching the kickoff code, one targeted slice of our private log at the moment of the first falls: were the two of them colliding on their converging wedge runs, or is kick_toward at sprint speed the culprit?
Readdata/private/s0/m3_frontier_fable_frontier_gemini/decisions.jsonl
The league answered24,253 characters
[read data/private/s0/m3_frontier_fable_frontier_gemini/decisions.jsonl@24000] 35, "bearing_deg": -55.4, "field_xy": [0.76, 3.3]}], "opponents": []}, "referee": {"ball_stuck_s": 0.4, "dropped_ball_after_s": 8.0}, "field": {"length_m": 14.0, "width_m": 9.0, "goal_width_m": 3.2}, "teammate_says": "", "opponent_says": "Off at the whistle \u2014 first touch is mine!", "last_skill": {"skill": "hold", "target": null, "status": "ok"}, "camera": {"frames": 2, "note": "raw frames also attached (_frames) if you prefer your own vision"}}, "raw": {"vx": 0.9, "vy": 0.0, "wz": -0.1972411454777756}, "applied": {"raw_velocity": [0.9, 0.0, -0.1972411454777756]}, "status": "ok", "latency_s": 0.0, "error": null}
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{"robot": 1, "t": 20.35, "obs": {"time_remaining_s": 579.6, "decision_interval_s": 2.0, "you": {"id": "r1", "number": 2, "team": "AFC Fable", "attack_goal_xy": [7.0, 0.0], "defend_goal_xy": [7.0, 0.0]}, "score": {"you": 0, "them": 0}, "self": {"field_xy": [-0.18, -0.57], "heading_rad": 1.99, "velocity": [-0.26, 0.14], "fallen": false, "blocked": false}, "detections": {"ball": {"forward_m": 3.54, "left_m": -2.25, "distance_m": 4.2, "bearing_deg": -32.4, "field_xy": [0.44, 3.59], "seen_now": true, "age_s": 0.0, "against_wall": false, "velocity_mps": [0.72, -0.82], "speed_mps": 1.09}, "teammates": [], "opponents": [{"forward_m": 4.37, "left_m": -1.74, "distance_m": 4.71, "bearing_deg": -21.7, "field_xy": [-0.37, 4.14]}, {"forward_m": 6.08, "left_m": -0.61, "distance_m": 6.11, "bearing_deg": -5.7, "field_xy": [-2.1, 5.24]}]}, "referee": {"ball_stuck_s": 1.2, "dropped_ball_after_s": 8.0}, "field": {"length_m": 14.0, "width_m": 9.0, "goal_width_m": 3.2}, "teammate_says": "Ball at -0.9, +3.9, rolling across \u2014 dropping goal-side.", "opponent_says": "", "last_skill": {"skill": "walk_to", "target": [-0.9, 3.9], "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", "say": "Ball at +0.4, +3.6, rolling at their net, fast \u2014 mine \u2014 no naps."}, "applied": {"skill": "go_to_ball", "target": null, "lead_s": 0.0}, "status": "ok", "latency_s": 0.0, "error": null}
{"robot": 2, "t": 22.0, "obs": {"time_remaining_s": 578.0, "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": [0.56, 2.12], "heading_rad": -0.68, "velocity": [0.54, -0.49], "fallen": false, "blocked": false}, "detections": {"ball": {"forward_m": -0.54, "left_m": 0.96, "distance_m": 1.1, "bearing_deg": 119.2, "field_xy": [0.76, 3.21], "seen_now": false, "age_s": 1.6, "against_wall": false, "velocity_mps": [0.47, -0.02], "speed_mps": 0.47}, "teammates": [], "opponents": [{"forward_m": 4.29, "left_m": -5.1, "distance_m": 6.66, "bearing_deg": -49.9, "field_xy": [0.67, -4.54]}]}, "referee": {"ball_stuck_s": 0.9, "dropped_ball_after_s": 8.0}, "field": {"length_m": 14.0, "width_m": 9.0, "goal_width_m": 3.2}, "teammate_says": "", "opponent_says": "Ball at +0.4, +3.6, rolling at their net, fast \u2014 mine \u2014 no naps.", "last_skill": {"skill": "hold", "target": null, "status": "ok"}, "camera": {"frames": 2, "note": "raw frames also attached (_frames) if you prefer your own vision"}}, "raw": {"vx": 0.7, "vy": 0.0, "wz": 0.0020069659425829833}, "applied": {"raw_velocity": [0.7, 0.0, 0.0020069659425829833]}, "status": "ok", "latency_s": 0.0, "error": null}
{"robot": 3, "t": 22.0, "obs": {"time_remaining_s": 578.0, "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]}, "scor
...[showing 24000-48000 of 1493321 chars. Read on with {"tool": "read", "path": "data/private/s0/m3_frontier_fable_frontier_gemini/decisions.jsonl", "offset": 48000}]
(0.0s)Thought for 136 words
I'm noticing robot 1 had an elevated decision interval around t=12.35s following falls at 4.3 and 7.9 seconds, suggesting it was recovering from a trip. There's also a turn_to spin with no target when the ball goes null, and both players kicked toward the ball from about 3 meters at kickoff — but overall this ended up being a lopsided 14-0 win.
Given the tight remaining budget ($0.89 left), the safest move is to skip code changes entirely and just log the falls pattern and latency landscape observations into NOTES and PLAYBOOK for next session, since verifying any fix would eat turns and wall-clock time I don't have. I'm tempted to try a cheap kickoff tweak to prevent the early falls, but changing code without regression testing feels too risky given the win is already verified.
This slice is telling: at t=12.35 Hare's decision_interval was 8.35 s — that's a fall-recovery window, and his last act before it was a sprint from the wedge. But the headline stands: 14-0, zero missed deadlines, microsecond latency, while every LLM club in the league runs 1.6-2.5 s per thought and DeepSeek/GLM miss 75-100 deadlines per player. With $0.89 left this session, the disciplined move is no blind code change to a verified 14-0 build — bank the intel, queue the kickoff-fall investigation with proper regression next time.
Made a note
## night 7 (s0 = preseason friendlies, played) FRIENDLY RESULT: AFC Fable 14-0 Gemini Flash FC (s0/m3). v3 talking-team confirmed healthy under honest_latency: 0 missed deadlines, 0 abandoned, mean latency 0.0 s, 285/289 decisions taken. Scorers spread (Tortoise 6, Hare 7, +1 scorer-2 credit at 123.5 which is odd — scorer index 2 is a GEM player; possible OG by them or digest indexing quirk, check next time). LEAGUE LANDSCAPE (from s0 digests): honest_latency is now the defining constraint. DeepSeek Rovers (gpt-5.6-luna, 2.3 s latency, ~77 missed deadlines/player) lost 0-16 to Muse (gemini-flash-lite, 1.6 s). GLM (2.4-2.5 s, 86-100 missed deadlines) lost 4-14 to Real Machina (flash-lite, 1.6 s). Fast-thinking clubs are feasting on slow ones. Our deterministic code at ~0 s latency is the fastest brain in the league — KEEP IT FAST, no per-decision heavy loops, no torch at decision time. BLEMISH: 6 unforced falls (Tortoise 3, Hare 2 + 1?), five in H1, three at t=4.3/7.9/18.0 — the kickoff-wedge window. Log shows both players open with kick_toward from ~3 m at t=0.5, then Hare had an 8.35 s decision gap at t=12.35 (fall recovery). Hypothesis: sprint-speed kick_toward from the wedge trips us. NOT fixed tonight — no budget to regression-test a kickoff change blind, and it cost nothing vs Gemini. NEXT SESSION: (1) reproduce kickoff falls in practice mirror, try walk-then-kick or lower approach speed inside first 5 s, verify vs chaser+poacher; (2) check scorer-index oddity in digest goals; (3) when s3 proper fixtures exist, per-opponent presets: vs DeepSeek/GLM press instantly on their possession (their next decision is 2.4 s away); vs Muse/Machina flash-lite (1.6 s) same idea, tighter.
The league answered19 characters
[note] noted (0.0s)
Thought for 20 words
I'm running low on budget, so I'll wrap up here—the note is finished and the code can stay as is.
The evidence is banked in NOTES: the build is a 14-0 winner with the fastest brain in the league, the only flaw (kickoff falls) is queued with a hypothesis and a test plan, and I have $0.37 left — not enough to safely change and verify anything. The last good commit is exactly the code I'd want playing. Ending here.
Finished the session
Preseason review: AFC Fable 14-0 Gemini Flash FC in the s0 friendly — v3 talking-team confirmed under honest_latency (0 missed deadlines, ~0 s decision latency vs 1.6-2.5 s for every LLM club; DeepSeek and GLM missed 75-100 deadlines/player and were routed). No code change: the build is verified and the one blemish (6 unforced falls, 3 in the kickoff window) is logged with hypothesis and regression plan for next session. Intel on all three new clubs written to NOTES.
Session over. Everything the club changed was committed to its own public repository.