Distill sessions
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".From its SKILL.md
npx -y skills add zl3311/alpha-mining --skill distill-sessionsAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
4.7 KB, ~1.1k tokens by cl100k_base, 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/*.mddata/sessions/*/data/knowledge/patterns/*.mddata/knowledge/dead_zones/*.mddata/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:
submissionscount,submittedlist, candidateverdictfields - 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
CANDIDATEis not a valid book status — normalize toPENDING- Session candidate schema uses
self_corr_value/self_corr_result/verdict(notself_corr) - Valid verdicts:
SUBMITTABLE,SUBMITTED,BLOCKED,BACKUP - Skill directory is
cloud-review(notsession-reviewas AGENTS.md hierarchy shows) - After submitting one template variant, siblings are blocked (mutual corr 0.90-0.95)
format_email_digest.pyreadsself_corr_valueandself_corr_resultfrom session candidates- BRAIN API is the source of truth for alpha status — always verify before setting ACTIVE
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.