Distill sessions

Skill zl3311/alpha-mining/.cursor/skills/distill-sessions

LLM-agent pipeline for formulaic alpha discovery on WorldQuant BRAIN, published with the full research archive it produced (archived)

Install

npx -y skills add zl3311/alpha-mining --skill distill-sessions

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What its author says it does

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Consolidate open draft mining session PRs into a single clean PR. Copies book entries, sessions, knowledge patterns, dead zones, and factors; deduplicates overlapping artifacts; verifies alpha statuses against BRAIN; runs bugbot iteratively; creates a consolidated PR; then closes the originals. Use when asked to "consolidate PRs", "distill sessions", "merge draft PRs", or "clean up mining PRs".

SKILL.md

4.7 KB, as published. Nobody here has run it

Distill Sessions

Consolidate accumulated draft mining-session PRs into one merge-ready PR.

Phase 0: Inventory

gh pr list --state open --draft

Identify mining session PRs (branch prefixes: session/, exp/, cursor/alpha-mining-session-*). Exclude non-session PRs (e.g. feature/, analysis scripts, infra).

For each PR, collect:

gh pr view <N> --json body,title,files --jq '{title, body, files: [.files[].path]}'

Build a manifest of artifacts to merge, grouped by type:

data/book/*.md
data/sessions/*/
data/knowledge/patterns/*.md
data/knowledge/dead_zones/*.md
data/factors/*.md

Phase 1: Create Branch

git checkout main && git pull origin main
git checkout -b chore/distill-draft-prs-<start_date>-<end_date>

Phase 2: Copy Artifacts

For each file in the manifest:

git show origin/<branch>:<path> > <path>

Create directories as needed (mkdir -p).

Conflict resolution:

Same file appears in multiple PRs → use version from latest session date
File already exists on main → diff branch version against main, merge new content

Phase 3: Deduplicate Knowledge

Scan new pattern files for overlap:

Same template/mechanism family → merge into single file
Preserve all learnings from both sources (anti-patterns, stabilizer tables, etc.)
Add exclusivity rules when template variants have mutual corr > 0.85

Phase 4: Verify Against BRAIN

uv run python3 scripts/brain_check.py --alpha-ids <space-separated IDs of all new book entries>

For each alpha, reconcile book entry with BRAIN source of truth:

BRAIN says ACTIVE → set status: "ACTIVE" in book entry
BRAIN says UNSUBMITTED → set status: "PENDING"
Never use CANDIDATE (not a valid book status)

Then propagate implications:

Update session metas: submissions count, submitted list, candidate verdict fields
Fix stale novelty claims (e.g. "field X absent from book" when it's now ACTIVE)
Mark sibling companions as BLOCKED if their primary variant is ACTIVE (template variants with mutual corr ~0.90-0.95 are mutually exclusive)

Phase 5: Update Docs

uv run python3 scripts/parse_frontmatter.py --dir data/book --field status,grade 2>&1 | rg -o 'status=\w+' | sort | uniq -c
uv run python3 scripts/parse_frontmatter.py --dir data/book --field family 2>&1 | rg -o 'family=\w+' | sort -u | wc -l

Update AGENTS.md "Submitted alphas" line with fresh counts. Do NOT update README (immutable superficial info only).

Phase 6: Validate

uv run python3 -m pytest tests/ -q
uv run python3 scripts/parse_frontmatter.py --dir data/book --field status,grade

All tests must pass. All book entries must parse without error.

Phase 7: Create PR

Stage, commit, push:

git add -A
git commit -m "chore: distill draft mining PRs <date_range>"
git push -u origin HEAD

Create PR with structured body (follow PR #67 format):

New book entries table (Alpha, Grade, Sharpe, Fitness, Self-Corr, Family, Session)
New sessions list
Knowledge base additions (patterns, dead zones, factors)
Merged branches list with PR numbers
Verification results (test count, book entry count)

Phase 8: Close Drafts

For each source PR:

gh pr close <N> --comment "Consolidated into #<new_pr_number>"

Phase 9: Bugbot Loop

Run bugbot review on the branch diff. For each iteration:

Fix all high-severity findings
Fix medium-severity findings that are factual errors (stale claims, schema mismatches)
Accept medium findings that are historical session documentation (accurate at session time)
Amend commit, force-push, re-run bugbot
Stop when no new high-severity findings remain

Known Gotchas

CANDIDATE is not a valid book status — normalize to PENDING
Session candidate schema uses self_corr_value / self_corr_result / verdict (not self_corr)
Valid verdicts: SUBMITTABLE, SUBMITTED, BLOCKED, BACKUP
Skill directory is cloud-review (not session-review as AGENTS.md hierarchy shows)
After submitting one template variant, siblings are blocked (mutual corr 0.90-0.95)
format_email_digest.py reads self_corr_value and self_corr_result from session candidates
BRAIN API is the source of truth for alpha status — always verify before setting ACTIVE