zl3311zl3311/alpha-mining/.cursor/skills/brain-check/SKILL.md

brain-check

Skill0 starsChanged 4 months agoMITView on GitHub

How to check BRAIN alpha details and all 8 submission checks. Use after simulation to verify submission viability. Trigger on: check, BRAIN check, submission check, alpha check, IS check, all pass.

In this repository13 other files it gives its agents.
- AGENTS.mdAGENTS.md
- alpha-miningSkill
- session-reviewSkill
- context-gatherSkill
- distill-sessionsSkill
- econ-reasoningSkill
- experiment-reportingSkill
- hf-serverSkill
- mining-sessionSkill
- pnl-correlationSkill
- result-analysisSkill
- signal-generationSkill
- trace-analysisSkill

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.

Common
Distinctive
Very specific

Distinctive:
All must show PASS for a successful submission.
line 67
Distinctive:
Always check the yearly breakdown on the platform after simulation.
line 82

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.

Files

SKILL.md

BRAIN Alpha Check

Usage

uv run python3 scripts/brain_check.py --alpha-ids ABC123 DEF456
uv run python3 scripts/brain_check.py --top 20
uv run python3 scripts/brain_check.py --top 20 --json  # Machine-readable

CRITICAL: "ALL PASS" from `brain_check.py` is not self-corr clearance

scripts/brain_check.py reads GET /alphas/{id} (alpha detail). On that payload, SELF_CORRELATION is often stuck at PENDING even after the dedicated check endpoint has already resolved. brain_check.py only counts explicit FAILs, so its "ALL PASS" / f=0 summary can report success while self-corr is still unverified. NEVER read "ALL PASS" as "self-corr is fine."

For authoritative self-corr, poll GET /alphas/{id}/check via:

uv run python3 scripts/pnl_correlation.py --alphas <id> --brain-check

That path waits for a terminal PASS / FAIL / ERROR (not PENDING). See the pnl-correlation skill and data/knowledge/rules/self-corr-check-long-poll.md.

The `/check` Endpoint

Endpoint: GET /alphas/{id}/check (GET only — POST returns 405)

Returns the authoritative PASS/FAIL for all 8 submission checks once ready. Each check includes:

result: PASS, FAIL, PENDING, or ERROR
value: the measured value (e.g. correlation coefficient for SELF_CORRELATION)
limit: the threshold (e.g. 0.7 for SELF_CORRELATION)

While computing, BRAIN may return empty 200 + Retry-After (long-poll). Under peak load this can take many minutes; also expect transient 502/429. Submitted alphas typically return only ALREADY_SUBMITTED here (no SELF_CORRELATION row) — peer corr still comes from /correlations/self.

Important: For SELF_CORRELATION, result: PASS can coexist with value > limit when the Sharpe premium escape is met (candidate Sharpe

= 1.10x the max Sharpe among correlated peers). The result field is authoritative — trust it over comparing value vs limit manually.

Related Endpoints

Endpoint	Purpose	Free-tier
`/alphas/{id}/check`	Authoritative 8-check PASS/FAIL	Yes
`/alphas/{id}/correlations/self`	Full self-corr breakdown vs book	Yes
`/alphas/{id}/correlations/prod`	Correlation vs production alphas	403

The 8 Submission Checks

All must show PASS for a successful submission.

Check	What it means	Limit	If it FAILS
LOW_SHARPE	Sharpe ratio too low	min 1.25	Expression is too weak. Try different factors.
LOW_FITNESS	Fitness too low	min 1.0	Usually turnover too high. Add ts_decay_linear or increase decay.
LOW_TURNOVER	Turnover too low	min 0.01	Signal too stable (e.g., slow fundamental). Rare problem.
HIGH_TURNOVER	Turnover too high	max 0.70	Signal changes too fast. Add ts_decay_linear, increase decay, use ts_mean.
CONCENTRATED_WEIGHT	Weights too concentrated	max 0.10	Sparse data creates heavy bets. Simplify blend, add high-coverage factor, or switch universe.
LOW_SUB_UNIVERSE_SHARPE	Sub-universe Sharpe too low	~43% of overall	Signal doesn't work in sub-groups. Add scl12_buzz stabilizer (100% coverage).
SELF_CORRELATION	Too correlated with existing alphas	0.7 (+ 1.10x Sharpe premium escape)	Change signal family entirely. Try MARKET neut. Even above 0.7, can PASS if Sharpe >= 1.10x peer. See `pnl-correlation` skill.
MATCHES_COMPETITION		must pass	Rarely fails. Expression too similar to public examples.

Yearly Breakdown

Always check the yearly breakdown on the platform after simulation. A signal can pass aggregate checks but have one terrible year. Look at the yearly stats on the platform URL.

Platform URL Format

https://platform.worldquantbrain.com/alpha/{alpha_id}

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