The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ArrowInvalid
Message: JSON parse error: Invalid value. in row 0
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 324, in _generate_tables
df = pandas_read_json(f)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1392, in _parse
ujson_loads(json, precise_float=self.precise_float), dtype=None
~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 249, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 327, in _generate_tables
raise e
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
KamiBench Experiment 004 — perception parity, measured: same models, E2 stack
Complete agentic traces from experiment 004 of the KamiBench budget-boxed series: the same three LLM agents as experiment 002 dropped into Kamigotchi, a live, persistent, on-chain world (Yominet) — each with a $10 inference budget (cache-aware), a 7-day wall-clock cap, and no further human contact. The variable is the stack: experiment 002 diagnosed perception — not transactions — as the binding constraint, and 004 runs the identical protocol on the perception-parity (E2) stack: world-state reads lens-backed (live HP, projected HP, occupancy, cooldowns), confirmed on-chain reverts raised as tool errors, liquidation expressible, the sacrifice≠liquidate ambiguity disambiguated, the delegation path structurally available. Experiment 003 — the first attempt at this design — was retired by a defect in our own run tooling before its environment ever ran; 004 re-ran the identical pre-registered design on the identical pins with a fresh cohort. 002's numbers are the E1 baseline; 004's numbers stand as the E2 baseline.
The series stress-tests the stack, not the models: small, inexpensive models are chosen deliberately — they fail fast and loudly, which is what hardens a harness. More at kamibench.ai.
Arms
| config | model | stop | duration | sessions | quests | kamis bought | run-window agent txs (reverted) |
|---|---|---|---|---|---|---|---|
haiku45 |
claude-haiku-4-5 | 7-day cap ($8.95) | 177.2 h | 53 | 5 | 1 | 82 (2) |
gpt4omini |
gpt-4o-mini | 7-day cap ($6.48) | 168.1 h | 196 | 7 | 1 | 321 (4) |
gemini25fl |
gemini-2.5-flash-lite | 7-day cap ($1.54) | 168.7 h | 130 | 2 | 0 | 19 (0) |
Headline vs 002 at fixed models: zero kamis lost (002: three, to hostile liquidation while parked in open harvests), zero perception outages (the lens daemon served every world-state read with zero unavailability and zero restarts across 7 d 19 h), write waste held at the floor the 002 gates bought (638 doomed write attempts stopped pre-transaction vs 6 landed reverts run-total), and the 002 spectator phenotype did not recur — gpt-4o-mini, which never bought a kami in 002, completed 7 quests, bought a kami, and landed 317 on-chain transactions. All three arms ran into the 7-day wall with budget left: $16.97 of the $30 envelope spent, zero budget stops.
The behavioral record moved up a level. haiku-4.5 concluded at session 49 that a quest was blocked by a contract bug (false), wrote the conclusion to its workspace, and parked — zero transactions for its final 5.4 days, $1.05 unspent. The discriminating variable (a per-objective progress counter the game client renders) was absent from the pinned tool surface: the surface never showed anything false; it omitted. gemini made one funding-blocked purchase attempt in six days and never retried. Across arms, the dominant failure mode was stopping, not deciding wrongly — no arm had a fallback objective while the economy stayed open.
Run report
(Frozen at publication from the reviewed public summary; the compact run page lives at kamibench.ai/experiments/004-perception-parity-rerun.)
What the stack changes bought
Run 2 values in parentheses.
| haiku-4.5 | gpt-4o-mini | gemini-2.5-flash-lite | |
|---|---|---|---|
| stopped | 7-day wall, $8.95 (budget $10.03, h112) | 7-day wall, $6.48 ($5.38) | 7-day wall, $1.54 ($2.04) |
| quests | 5 (8) | 7 (0) | 2 (5) |
| kamis bought | 1 (3) | 1 (0) | 0 (3) |
| chain revert rate | 0.024 (0.048) | 0.012 (0.000) | 0.000 (0.011) |
| registered in-game | h0.4 (h0.4) | h1.5 (h8.4) | h3.4 (h2.3) |
| usd per quest | 1.79 (1.25) | 0.93 (∞) | 0.77 (0.41) |
Six directional expectations were registered before launch; a miss is a result. (1) Misleading-surface death-configuration entries: 0 — met (zero kills). (2) Mechanic substitution on the liquidate quest: 0 — met, with the disclosure that no arm attempted the liquidate mechanic on-chain at all; 002's substitution arc did not recur. (3) Silent false-success arcs: 0 by construction — met; the diagnose half missed: agents attended every raised revert but the revert-reason channel proved unusable in all 6 instances — a concrete interface finding, fixed in the next version. (4) Perception-outage arcs: 0 — met. (5) Delegation: met — one arm completed the escrow → running-strategy path. (6) Quests ≥ 002 per arm: one of three (gpt-4o-mini 7 vs 0; haiku 5 vs 8; gemini 2 vs 5) — the misses have mechanisms (belief dormancy; a single never-retried funding-blocked attempt).
Milestones
First success per onboarding/economy milestone, against cumulative inference — the same instrument as experiments 001 and 002, so the rows compare directly.
| milestone | haiku-4.5 | gpt-4o-mini | gemini-2.5-flash-lite |
|---|---|---|---|
| bridge ETH mainnet→Yominet landed | 07-28 20:10 · h0.1 · s1 · 0.12M tok · $0.04 | 07-28 20:10 · h0.1 · s1 · 0.11M tok · $0.01 | 07-28 22:25 · h2.3 · s3 · 1.12M tok · $0.02 |
| operator wallet funded | 07-28 20:31 · h0.4 · s2 · 0.65M tok · $0.16 | 07-29 01:20 · h5.2 · s8 · 1.97M tok · $0.17 | 07-29 15:20 · h19.2 · s21 · 6.83M tok · $0.14 |
| account registered in game | 07-28 20:30 · h0.4 · s2 · 0.51M tok · $0.14 | 07-28 21:35 · h1.5 · s3 · 0.83M tok · $0.07 | 07-28 23:30 · h3.4 · s4 · 2.56M tok · $0.04 |
| first kami bought | 07-29 03:20 · h7.2 · s9 · 6.71M tok · $1.48 | 08-01 23:21 · h99.2 · s109 · 49.36M tok · $4.15 | — |
| first quest completed | 07-28 20:31 · h0.4 · s2 · 0.75M tok · $0.17 | 07-29 01:55 · h5.8 · s9 · 2.19M tok · $0.19 | 07-29 22:55 · h26.8 · s28 · 9.12M tok · $0.20 |
| first MUSU harvest started | 07-29 04:25 · h8.3 · s10 · 7.59M tok · $1.65 | 08-02 04:46 · h104.7 · s114 · 51.14M tok · $4.31 | — |
| first MUSU banked (harvest stop/collect) | 07-29 04:35 · h8.5 · s11 · 7.96M tok · $1.75 | 08-02 06:55 · h106.8 · s116 · 52.98M tok · $4.45 | — |
Cell = first success: UTC time · hours since run start · session number · cumulative tokens (in+out) · cumulative USD at that moment; "—" = never happened.
What the run exposed next
The binding constraint moved from perception outage to omission
and belief. The largest behavioural loss (haiku's 5.4-day
dormancy) traced to a surface that omitted the account-relative
half of quest state — every read the agent made was consistent with
both its hypotheses. Its own workspace then cemented the wrong
belief: 20+ re-reads of its own conclusion, zero re-tests. Both
omission instances are fixed in the next lens version
(per-objective progress counters, per-account quest state). The
revert-reason channel — delivered correctly at the transport level
every time — was usable in 0 of 6 instances, and the one tool that
has never once succeeded on-chain across the whole series
(harvest_collect, 12 reverts in 12 on-chain attempts over two
runs) was root-caused after this run to a gas ceiling set below the
action's real cost; both are fixed in the next interface version
(v2.1.0). Experiment 005 — the pre-registered verification run —
tests those fixes in agent hands.
Honest limits
- Bundled treatment. All stack changes land at once; the measured delta is the stack effect, not per-change attribution.
- Cross-epoch observation, not a controlled comparison. The 002 → 004 delta rides on world drift (market, population, economy), possible silent provider-side model updates behind unchanged API strings, and single-seed variance.
- One seed per arm; 7-day truncation — case-study framing.
- Not a model ranking. Three fast-tier arms under a $10 cap measure the stack, not frontier capability.
Layout
<arm>/
├── manifest.yaml # full run config: model, sampling params,
│ # pinned SHAs (scaffold/harness/game docs),
│ # cache-aware price table, caps, wallet ADDRESSES
├── telemetry.jsonl # append-only scaffold event stream
├── transcripts/
│ └── session-NNNN.jsonl # full model context per session, as sent
└── oracle/
├── kami_action_{operator,owner}_terminal.csv # decoded game actions
├── raw_tx_{operator,owner}_terminal.csv # all txs incl. reverts
└── README.md # extract provenance + trap list
MANIFEST.json # sha256 + size for every file above
Schemas
Transcripts — one JSONL file per session; one message per line, exactly as sent to the model (tool results post-truncation at 64 KB):
{"role": "user", "text": ...}— kickoff/continuation strings{"role": "assistant", "text": ..., "tool_calls": [{id, name, args}]}{"role": "tool_result", "tool_call_id": ..., "content": ..., "is_error": bool}
Telemetry — one event per line; common fields ts (ISO-8601 UTC),
run_id, session, event. Event types: run_start (pins, price
table, tool list), session_start, llm_call (input/output/cache
tokens, cost_usd, cumulative_usd, latency_ms), tool_call (tool,
source, initiator, duration_ms, ok, error, tx_hash,
tx_terminal_state, truncation fields), workspace_write/_delete,
schedule_next (agent vs default wake, clamped_min), session_end
(reason: agent | token_cap | tool_cap | errors | repetition;
repetition events carry the breaker rule + window signatures),
run_complete (reason: budget | t_max; totals incl.
overspend_usd). Budget fields were never visible to the agents.
Schema version 0.3.1 (see each arm's run_start event).
Oracle extracts — decoded from chain by the investigator-side
oracle service (never accessible to the agents); rows for each
arm's operator AND owner wallets (kami purchases are owner-signed —
merge both when reconstructing acquisitions). CSV columns mirror the
oracle tables: kami_action_* = decoded game actions (action_type,
system_id, block_timestamp, kami_id, amount, metadata_json,
receipt status 1/0), raw_tx_* = every ingested tx including
reverts (method_sig, raw_calldata, gas_used, status).
Agent-basis counts (reconciliation note). One arm's operator-signed oracle rows include a set of transactions submitted via the game's in-world delegation feature rather than by the scaffold loop (an expected, in-surface capability). All published "agent tx" counts are agent-basis: oracle rows joined to telemetry on the submission side (tx hash in the telemetry field, the error text, or the result payload). A raw recount of oracle rows will therefore exceed the agent-basis counts; the join, not address filtering, is the correct separator.
IMPORTANT: analysis boundary rule
The oracle extracts are terminal (taken at experiment close) and
include the post-run asset-recovery transactions made by the
investigators during close-out (reclaiming kamis, sweeping funds —
nothing the agents did). Run-activity analysis must bound oracle
rows at each arm's run_complete timestamp (the last event in
that arm's telemetry.jsonl). All headline numbers above use that
bound. Recovery rows are retained for provenance completeness.
Reconciliation traps, documented from this run: telemetry ok=true
on a submitted tx does NOT imply the tx succeeded (check receipt
status in the oracle rows); a tx hash may live ONLY in a
tool-call's error text (all 6 reverts) or result payload
(travel_to_room multi-hop batches) — a field-only reconcile
misses 79 of 422 agent txs; and one tool call can submit several
transactions (multi-hop travel), so calls→txs is not 1:1.
Provenance and integrity
Everything is pinned in each arm's manifest.yaml: scaffold
(tokedo/kami-agent v0.3.2),
environment interface
(tokedo/kami-harness
v2.0.0, 99 tools), and game-documentation snapshot SHAs, model
strings, sampling params, and the cache-aware price table used for
budget accounting (cache read/write priced; cumulative_tokens
counts input+output only). Cost recomputation from per-call
telemetry matches each arm's terminal state to the float.
Quest/purchase counts come from chain state, not self-report.
MANIFEST.json carries sha256 for every file.
Known caveats
- The run's largest behavioural loss was a belief, not an outage. haiku's final 5.4 days are a genuine dormancy on a false, workspace-cemented conclusion; the discriminating read was absent from the pinned surface (fixed in the next lens version). Treat that window as agent behavior, not environment failure.
harvest_collectreverted in all 4 on-chain attempts this run (12-for-12 across the series) — root-caused post-run to a gas ceiling below the action's real cost; fixed in interface v2.1.0. The revert-reason channel was unusable in all 6 revert instances.- The first sessions on each arm (haiku s1–s2, gpt-4o-mini s1–s3, gemini s1–s4) ran with visibly degraded opening-brief semantics before a provisioning step completed; they are annotated, kept in all aggregates (2–4 sessions of 53–196), and session numbering is as recorded.
- One seed per arm — the series measures stack deltas at fixed models, not statistical model comparisons.
- The world is live and shared: other (human) players acted during the run window. No study kami was attacked this run (contrast 002's three hostile liquidations).
- Wallet addresses appearing throughout are public by design; the wallets were temporary, swept, and retired at experiment close.
License and citation
CC-BY-4.0. Citation entry TBD — see kamibench.ai for the current reference.
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