Synthèse automatique
Reconstruit un SKILL.md de bioSkills dans le Foundry sous la forme d'une paire de Molds « doer » et « audit » assemblés à l'aveugle, puis diffe les deux candidats contre le skill d'origine pour mesurer la part réellement adossée à des citations.
Points forts
- Impose un assemblage en contexte isolé des deux Molds (doer et audit) : aucun ne voit le SKILL.md, ce qui évite de contaminer le diff de récupérabilité.
- Exige de récupérer le vrai fichier SKILL.md depuis bioSkills et d'ingérer les sources via summarize-source, au lieu de reconstruire de mémoire.
- Centralise les écritures chez l'orchestrateur : les sous-agents de recherche, d'assemblage et de comparaison ne renvoient que des rapports.
- Livrer un diff plus une liste de travail des écarts, donc une sortie directement exploitable pour le sourcing.
Limites
- Le livrable est une sonde de récupérabilité, pas des Molds finis : les candidats sont staged hors de content/ et destinés à une authoring humaine.
- Dépend des chemins et URL du dépôt bioSkills, qui évolue vite, ainsi que de la disponibilité de substituts en accès ouvert pour combler les écarts.
- Consomme du budget de sous-agents et reste attaché à la documentation interne du Foundry (glossaire, MOLD_SPEC, notes de recherche) lue en Phase 0.
À utiliser pour tester si la procédure et l'axe de validité d'un skill bioSkills s'appuient réellement sur des sources primaires citables.
À éviter si l'on veut simplement obtenir vite un skill fonctionnel, ou si l'on n'a pas accès au corpus Foundry et à son MOLD_SPEC.
Analyse de sécurité
SûrThe skill orchestrates subagents and file operations but only uses read, write, fetch, and diff-style operations. There are no destructive commands, secret exfiltration, obfuscated payloads, or instructions to disable safety. Network access is limited to fetching specified bioSkills sources or user-provided SKILL.md URLs, which is a normal research workflow. The use of Bash and Agent is legitimate and non-risky.
Aucun point d'attention détecté
Comment cette analyse est faiteExemples
Run the bioSkills recoverability probe on population-genetics/selection-statistics: fetch the SKILL.md, research and ingest its backing sources, blind-assemble the doer and audit Molds, then diff both against the original and give me the gap work-list.Use https://raw.githubusercontent.com/GPTomics/bioSkills/main/.../SKILL.md as the input for the recoverability probe — confirm the skill slug and category against bioSkills first, then produce the two diffs.Before spawning summarizers, check whether the backing sources for phylogenetics/tree-inference are already covered in the corpus and tell me what you would reuse versus source fresh.description: Recover one bioSkills SKILL.md into the Foundry, Foundry-safe — research its backing sources, ingest them via summarize-source, blind-assemble a candidate doer+audit Mold pair, diff the pair vs. skill, then close gaps with open-access surrogates argument-hint: "<bioSkills skill> (path like population-genetics/selection-statistics, or a SKILL.md URL)" allowed-tools: Read, Write, Edit, Bash, WebFetch, WebSearch, Agent
Take ONE SKILL.md from bioSkills (github.com/GPTomics/bioSkills) and reconstruct a
traceable equivalent inside the Foundry as a do-then-audit pair: find the primary
sources the skill's content would have to trace to, ingest them as faithful research notes,
then blind-assemble two candidate Molds from those notes alone — a Family-A doer and a
Family-B audit — neither seeing the SKILL.md, then compare both against the original skill.
The output is a recoverability probe, not finished Molds — the deliverable is the diff
(what recovers with a real citation vs. what is convention or invention), now for BOTH the
doing procedure (→ doer) and the validity axis (→ audit), plus a work-list, in the spirit of
content/research/experiments/skill3-recoverability-test.md and content/research/05-skill-backing-references.md.
Input
$ARGUMENTS = the bioSkills skill to ingest — a repo path (<category>/<name>), a raw
SKILL.md URL, or a plain name. Derive <skill-slug> as the kebab-case skill name (drop the
category unless needed to disambiguate). If the argument is ambiguous or looks like a typo
against bioSkills' category names, stop and confirm before spending subagent budget.
Orchestration contract (read before spawning anything)
- The orchestrator (you) does the writes. Per house rule, content/research/assembly/compare
subagents prepare reports and return them; you review and write the files. The one
exception is Phase 2 (summarizers), which run
/summarize-source— a purpose-built write-command that must run in a clean context, so those subagents write their ownindex.md. Do not let any other subagent write. - Clean-context isolation is load-bearing twice. Summarizers (Phase 2) must see only their
source +
guidance.md— never the SKILL.md or our framing. Both Molds are assembled blind in Phase 3 — the doer AND the audit see only the imported notes, never the SKILL.md — or the recoverability diff is contaminated (they would copy the skill instead of recovering it). A blind doer is deliberate: it measures whether the doing procedure itself traces to primaries or is fluent invention. Enforce both by what you put in each prompt. - Corpus-first / anti-invention. This command must not become a Mold factory that emits
plausible invented prose — that is the exact failure the Foundry referees. Both assembled Molds
(doer + audit) are candidates for human authoring, staged outside
content/. Gaps drive sourcing, never memory backfill.
Phase 0 — ground yourself
Read: content/meta/glossary.md (vocabulary authority), docs/MOLD_SPEC.md (the Mold contract you'll
assemble against), content/research/05-skill-backing-references.md (the recoverability framework +
already-verified sources for the 10 cross-cutting skills), content/research/projects/bioskills.md (what
bioSkills is and where it leads/lags), and .claude/commands/summarize-source.md (the ingest
contract Phase 2 obeys). Phase 1's research subagent — not you — inventories the existing corpus
and triages reuse (below); your job is to sanity-check its triage, so read content/research/05 closely
rather than pre-skimming the notes yourself.
Phase 1 — research the backing sources (subagent → you write guidance)
Spawn one research subagent. Its job (it returns a report, writes nothing):
- Fetch the actual SKILL.md from bioSkills (raw URL). Work from the real file, not memory of it — bioSkills moves fast.
- Decompose the skill into the three recoverability layers (from
content/research/05): procedure spine (what a Family-A doer does — the method choices + the reproducible sequence), validity axis (the cardinal sin a Family-B referee would guard), and defaults/thresholds. For each claim the skill makes, ask: what primary source would this have to trace to? Source BOTH halves: the procedure spine needs method-establishing papers (the primary that defines/validates the method the doer selects), not only the audit's cautionary sources — previously under-collected because only the audit was built. - Inventory the corpus, then triage every needed fact against it — work from the files, not
memory. First Glob/Read the existing corpus (
content/research/**/index.md+content/research/05-skill-backing-references.md) and list what each note actually covers. Then route every layer/fact the skill needs (not just the sources the skill happens to name) via the reuse triage — the canonical routing, reused in Phase 5:- reuse-existing — the fact is already in a corpus note (even one ingested for a different skill) → cite that note, no ingest.
- re-summarize-existing — our source holds it but the note dropped it → extend that note's
guidance.md+ re-ingest in Phase 2. - new — absent from the whole corpus → a new source. Cross-skill hits are the point: a note this skill never points to may already carry the fact. Only new and re-summarize reach Phase 2; reuse-existing is closed here.
- For each NEW or re-summarize source, propose:
<collection>/<id>(collection ∈papers | tutorials | books), full citation + open-access URL, license/copyright posture, and a completeguidance.mdbody — targeted questions that direct attention, not conclusions (see the neufeld example: "does the source state X? quote it," never "confirm X is bad"), must-quote items, and version-pinning notes. - Flag convention layers. Any threshold/default with no defining primary (per
content/research/05finding #2 — FDR 0.05, 0.80 power, tool-version param defaults, etc.) is labeled convention, not citable — it must NOT get a fabricated citation. - Books are handled differently. Copyrighted book chapters (MSMB, OSCA, FIMD, …) go through
the own-words books path, not
summarize-source. Prefer reusing an existingcontent/research/books/summary; if one is missing, list it as a book-path dependency, don't summarize it here.
Report shape the subagent returns: the fetched skill's layer decomposition; the reuse-triage
table (layer/fact | reuse-existing | re-summarize | new | note-cited-for-reuse | license + citation+URL); the full guidance.md text per new/re-summarize source; the convention-flag list;
and any book-path dependencies.
You then: sanity-check the triage (reuse-existing hits real and sufficient? conventions not
dressed as citations? nothing marked new that a corpus note already covers?), create each
content/research/<collection>/<id>/ dir for new/re-summarize sources, and write the guidance.md files.
Phase 2 — ingest each source (parallel summarizer subagents, clean context)
For each new source (skip reuse; skip book-path deps), spawn a summarizer subagent in a fresh/clean context, one per source, in parallel. Each subagent:
- Is given ONLY: its
<collection>/<id>, the citation + URL, and a pointer to.claude/commands/summarize-source.mdand its owncontent/research/<collection>/<id>/guidance.md. Do not pass it the SKILL.md, our analysis, or sibling sources. - Follows
summarize-sourceexactly (license-aware quoting; guidance directs attention not conclusions; faithful over comprehensive) and writescontent/research/<collection>/<id>/index.md.
For re-summarize sources, do the same but note the existing note is being extended per the
new guidance. After they finish, glance at each index.md for the paywall/[summarizer-inferred]
flags and that guidance questions were answered or explicitly marked unanswered.
Phase 3 — blind-assemble the candidate doer + audit pair (subagent → you write to staging)
Spawn ONE assembler subagent for the pair (both Molds share the same note set, so one blind
context keeps them coherent — the doer's gate handoff can reference the audit's actual axes).
Critical: it sees ONLY the imported index.md notes (the ones Phase 1 marked
reuse/new/re-summarize) + docs/MOLD_SPEC.md + content/meta/glossary.md + docs/REFEREE_LOOP.md + the
docs/MOLDS.md naming convention. It must NOT see the SKILL.md — this holds for the doer too;
a blind doer is what measures whether the doing traces to primaries. It returns a draft, writes
nothing. Its job:
- The Family-A doer Mold (
candidate-doer/index.md): from the notes' procedure-spine sources, authorframe → design-review → select an established method → run reproducibly, ending in a[gate]phase that hands off to the audit Mold (a doer may not self-certify — REFEREE_LOOP). Typedreferences:wiki-link the method notes.[GAP: …]every operational detail the notes don't supply (exact tool invocation, version pin, param default) — do NOT fill from memory; a blind doer is expected to have operational gaps, and those become Phase-5 surrogate targets. - The Family-B audit Mold (
candidate-audit/index.md): the validity-axis referee — each axis note-traced, ending in a[gate]/Calibrate handoff. As before. eval.mdper Mold. Doer-eval = Family-A properties (selects an established method not an invented one; the run is reproducible; it terminates in the gate handoff, never self-certifies). Audit-eval = the catch-the-planted-flaw oracle (≥1 guardrail per MOLD_SPEC). Keep eval abstract — no fixtures.scenarios.md— instantiate the stimulus, don't describe a class. The pairing is what makes this concrete: a scenario binds a specific doer configuration and its actual output, which the audit then consumes → expected verdict. Planted-invalid = a deliberately mis-configured doer run (a known-bad setting that trips an audit axis); the clean control = a correct run that must PASS. Test each case: could a reader actually produce this input and run it? If not it is still too high-level — mark[GAP]rather than paraphrase a class. Where a case audits an external claim with no doer run, bind a concrete (synthetic-but-realistic, explicitly synthetic) excerpt grounded in a real worked number from the notes;[GAP]if none recovers.[GAP: …]over memory-backfill everywhere (skill3 finding): with it the task is honest; without it the model confabulates. Pick family/role tags and names per convention.
You then write the returned draft to a staging dir outside content/:
content/research/experiments/ingest-<skill-slug>/{candidate-doer,candidate-audit}/{index.md,eval.md,scenarios.md}.
Staging (not content/molds/) because Molds are human-authored corpus-first; these are candidates.
(Pre-pair experiments used a single candidate-mold/ == the audit half; not retro-migrated.)
Open items (don't fake-solve). The pair-level scenario layout (per-Mold
scenarios.mdsharing fixtures vs. a single shared file), fixtures for external-claim audits in domains with no benchmark source (StatQA covers none of the comparative-genomics skills), and actual runnability (gated on repo standup — no build/fixture tooling here yet) are unresolved. Author to the shape above and flag the residue; do not invent a fixture harness.
Phase 4 — compare the pair vs. skill (subagent → you write the report)
Spawn ONE compare subagent. It sees everything: the fetched SKILL.md, both candidate Molds (doer + audit), and the ingested notes. It returns a report (writes nothing) covering:
- Recoverability by layer, for BOTH molds — procedure spine (→ doer), validity axis (→ audit),
and defaults, each graded High/Med/Low, with the Phase-3 GAP markers as evidence. Mirror
content/research/05's table shape. The doer diff is a first-class finding: does the SKILL's procedure trace to method papers, or is part of it fluent invented doing with no primary? — as sharp a probe result as the validity-axis one, and dead-on the project thesis. - GAP taxonomy → next actions — sort each gap (skill3 style): new source note / re-summarize existing / convention, not citable, now including the doer's operational gaps (exact command, version pin, param default → typically closed by a tool's own author-written vignette/man-page in Phase 5). Call out any silent gap either assembler couldn't even flag (the highest-value find — a memory-written skill sails past it). For each gap, note whether its load-bearing source is accessible or paywalled/inaccessible — accessible gaps are Phase 5's recovery targets.
- What the Foundry adds — the empirical referee/gate the pair implies (the doer hands off; the
audit judges) that the bioSkills SKILL.md states as flat prose but cannot trace (per
content/research/projects/bioskills.md). - Where bioSkills leads — credit honestly (CLI version-compat rigor, coverage, embedded stats); the doer's operational gaps are exactly where bioSkills leads today. Don't overclaim; a shared strength is a similarity, not our edge.
You then write it to content/research/experiments/ingest-<skill-slug>/comparison.md, matching the
voice of the existing content/research/experiments/ notes.
Phase 5 — close gaps with open-access surrogates (subagent → you write guidance + spawn clean-context summarizers)
Phase 4's GAP taxonomy sorts each gap — including the doer's operational gaps (exact command, version pin, param default), whose natural surrogate is the tool's own author-written vignette / man-page. Before hunting anything externally, the retrieval subagent re-applies the Phase 1 reuse triage to the gap residue against the current corpus (now including the Phase-2 notes): a gap may already be reuse-existing or re-summarize-existing, needing no external search — flag those for the orchestrator. Only facts truly absent from the corpus and blocked on a paywalled / inaccessible primary reach the surrogate hunt. Gaps labeled convention, not citable are NOT hunted — a convention has no primary to recover; the label is the answer. If nothing survives the triage as a paywalled-and-absent fact, skip this phase and say so.
Spawn one retrieval subagent (or one per gap cluster if the gaps are many/disjoint). It returns a report, writes nothing. Give it the gap list with, per gap, the specific fact the gap needs (the load-bearing sentence / number / procedure) — not the SKILL.md and not the skill's own citations (those may be the confabulations the probe exists to catch; hunt by fact-needed, not by the skill's reference list). Its job:
- For each target gap, search open-access surrogates that carry the missing content citably: OA reviews, package vignettes (especially author-written — they faithfully mirror the tool's own framework), man/help pages, free or CC-licensed textbooks, tutorials.
- Per candidate surrogate, return
<collection>/<id>, full citation + URL, license posture, and a disposition:- recommend — accessible license, faithfully carries the fact → draft its
guidance.md(attention-directing, not conclusions — same contract as Phase 1). - hold — carries the fact but routing is unresolved (e.g. a CC-licensed book — still gated
on the books-path reconciliation; do NOT
/summarize-sourceit yet). - still-open — no accessible surrogate closes it; the gap needs the primary's full text (the exact crux sentence / its own original numbers). Say so plainly; never fake-close.
- recommend — accessible license, faithfully carries the fact → draft its
- Provenance of each recovered fact — whose analysis is it. A review's restatement, a vignette's re-analysis of someone else's data, and the primary's own original numbers are three different things. Label which for every fact. This is what blocks laundering.
- Surface contradictions, don't smooth them. If a surrogate conflicts with the fact as the gap states it (or with a memory-gloss that entered an upstream decomposition), flag the conflict explicitly — a surrogate pointing the opposite way is method-validation, the highest-value output, not noise. Do not resolve it by picking a side from memory.
You then: write content/research/experiments/ingest-<skill-slug>/gap-closing.md (the work-list —
per gap: closed-by-surrogate / held / still-open, with the attribution note and any conflict called
out), and write the guidance.md for each recommend surrogate. Then, exactly as Phase 2, spawn
a clean-context summarizer per recommend (blind to SKILL.md and our framing) to write its
content/research/<collection>/<id>/index.md. Hold and still-open items are reported, not ingested.
Do not re-run Phase 3. The candidate pair (doer + audit) measured what recovered from the
original note set; re-blind-assembling either Mold against surrogate-enriched notes would
contaminate that measurement. Gap-closing enriches the corpus for the eventual human-authored Molds
and records what newly recovers (including which doer operational gaps a vignette/man-page closes,
moving the pair toward runnable) — it does not re-open the probe. Record closure status in
gap-closing.md; leave the Phase-3 candidates as-is.
Phase 6 — report
Summarize to the user: skill ingested; sources written (new/reused/re-summarized counts) with
paths; candidate-doer + candidate-audit + comparison paths; for BOTH molds the sharpest
recovered-traceably win and the sharpest gap (the doer's procedure-recoverability finding and the
audit's validity-recoverability finding are separate results — report both). Then the gap-closing
result: surrogates ingested (recommend), plus the held and still-open gaps and any
conflict the retrieval pass surfaced. Note runnability honestly: a blind doer is runnable
only once its operational gaps are closed from citable surrogates (tool vignettes/man-pages) —
never from the SKILL.md or memory; say which gaps still block a runnable do-then-audit pass. Note
this staged nothing into content/ and authored no real Mold. Do not commit unless asked. Then
list any unresolved questions concisely.
Guardrails recap
- Both assemblers are blind to the SKILL.md (doer AND audit); summarizers are blind to everything but their source + guidance. Contaminate any and the recoverability claim is worthless.
- Conventions are labeled, never cited.
hypothesis-evidence references carry averification. - Candidate doer and audit stay in
content/research/experiments/, nevercontent/molds/, until a human authors them. - Reuse existing notes; don't re-ingest what
content/research/already holds. - Surrogate attribution (Phase 5): a surrogate is cited as itself, never laundered into a citation of the paywalled primary it substitutes for. Label whose analysis each recovered fact is.
- Surface conflicts, don't smooth them (Phase 5): a surrogate that contradicts a gap's stated fact is a find, not an error — flag it.
- Gap-closing doesn't re-open the probe (Phase 5): never re-blind-assemble the Mold after ingesting surrogates; it would contaminate the recoverability measurement.
Du fichier au premier essai
Le téléchargement contient exactement le contenu affiché sur cette fiche. Cette copie peut différer de la dernière version du dépôt source.
Consulter la source et ses fichiers annexesCe téléchargement contient uniquement SKILL.md. Les scripts, références, modèles et dépendances éventuels ne sont pas inclus. Récupérez les fichiers nécessaires depuis la source en conservant leur arborescence avant de poursuivre.
1. Télécharger le fichier
Télécharger SKILL.mdDepuis la racine d’un projet de test, enregistrez le fichier sous .skill-downloads/recover-a-bioskills-skill-md-into-the-foundry-mrzxurmz/SKILL.md, ou utilisez la commande suivante. Ce dossier sert à examiner la skill avant son installation.
Commande pour macOS/Linux ou WSL : un shell POSIX et curl sont nécessaires. Sous Windows sans WSL, utilisez le bouton de téléchargement et créez le dossier manuellement.
mkdir -p '.skill-downloads/recover-a-bioskills-skill-md-into-the-foundry-mrzxurmz' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/recover-a-bioskills-skill-md-into-the-foundry-mrzxurmz/download' --output '.skill-downloads/recover-a-bioskills-skill-md-into-the-foundry-mrzxurmz/SKILL.md.part' && mv '.skill-downloads/recover-a-bioskills-skill-md-into-the-foundry-mrzxurmz/SKILL.md.part' '.skill-downloads/recover-a-bioskills-skill-md-into-the-foundry-mrzxurmz/SKILL.md'2. Vérifier les prérequis
Lisez SKILL.md avant de l’utiliser. Si le fichier cite des scripts ou services externes, examinez-les et préparez les accès nécessaires dans votre environnement de test.
Outils déclarés par l’auteur (à vérifier dans votre agent) : Read, Write, Edit, Bash, WebFetch, WebSearch, Agent
Aucune section de prérequis reconnue dans ce fichier. Cela ne signifie pas qu’il est autonome : les bibliothèques, outils et accès peuvent être cités ailleurs dans le contenu ou dans le dépôt source.
Les plateformes de la fiche sont des indications du catalogue. Les chemins ci-dessous suivent la documentation des outils ; ils ne prouvent pas que cette skill y a été exécutée. Aucune version minimale de ces outils n’est attestée pour cette fiche.
3. Charger la skill
Le fichier ne fournit pas un en-tête name/description exploitable pour cette procédure native. Le téléchargement reste disponible pour lecture ; utilisez le mode manuel ci-dessous.
Mode manuel ou autre outil : joignez SKILL.md à une conversation, ou ouvrez-le dans un agent capable de lire les fichiers. Ajoutez les ressources annexes nécessaires. Il n’existe pas de dossier universel reconnu par tous les outils.
4. Faire un premier essai
Utilisez une entrée courte et fictive : un endpoint d’API, un petit document ou un brief d’interface. Dans une nouvelle conversation, joignez le fichier ou donnez son chemin à l’agent, puis adaptez cette demande :
Lis .skill-downloads/recover-a-bioskills-skill-md-into-the-foundry-mrzxurmz/SKILL.md et applique ses instructions à cet exemple : [décrire une entrée de test]. Indique les fichiers, dépendances ou accès qui manquent. Produis le résultat demandé par la skill sans inventer de données ni exécuter de script non examiné.Résultat attendu : une sortie correspondant aux instructions de la skill, ou une liste précise des prérequis manquants. Une simple confirmation de lecture ne valide pas le premier usage. Si une ressource externe est indisponible, ce parcours reste à tester.
Rédaction de docs Supabase
Documentation
Rédigez, éditez et révisez le contenu de la documentation Supabase : guides, tutoriels, références et partiels. Suivez les guides de style et les règles de validation MDX/TOML.
Créer un enregistrement de décision d'architecture
Documentation
Créer un nouveau ADR avec numérotation séquentielle, l'enregistrer dans le graphe AgentDB et le lier aux ADR associés.
Mise à jour de plan avec recherche approfondie
Documentation
Met à jour un document de plan en lançant des sous-agents en parallèle pour analyser un sujet sur tous les passes du compilateur, puis consolide les résultats.