---

description: Score how well we could build a Foundry mirror of an external skill (e.g. a bioSkill) across the four mold-eval rubrics — defers research to per-axis subagents, delegates grading to the rubric files argument-hint: "<external skill> (bioSkills path like comparative-genomics/synteny-analysis, a SKILL.md URL, or a local path)" allowed-tools: Read, Write, Edit, Bash, WebFetch, WebSearch, Agent

/assess-external-skill

Take ONE external skill (a bioSkills SKILL.md or equivalent) and produce a four-axis scorecard answering: how well could we construct a Foundry mirror of this skill? The axes are the mold-eval rubrics — Operability, Assessability, Traceability, Refereeability. This command does not restate their criteria: it fans research out to subagents and delegates every grade to the rubric file. Split of labor:

• The rubric owns the grading criteria (dimensions, bands, open questions) — the authority.
• This command owns the research protocol (what evidence to gather, how to fan out) — nothing more.

Output is a scorecard, not a mirror — a feasibility read that drives further work.

Relation to /ingest-bioskill: that command is the deep Traceability probe (ingests sources, blind-assembles molds, diffs). This is the fast scorecard across all four axes; its Traceability pass is a lightweight triage that escalates to /ingest-bioskill when a real recoverability verdict is needed. Do not re-run the ingest here.

Input

$ARGUMENTS = the external skill: a bioSkills <category>/<name>, a raw SKILL.md URL, or a local path. Derive <skill-slug> (kebab-case name). If ambiguous or a likely typo vs. bioSkills' categories, stop and confirm before spending subagent budget.

Phase 0 — ground (you)

Read content/meta/glossary.md (vocabulary) and the four axis files under content/research/mold-eval/rubrics/ plus its README.md — the vector-not-GPA rule and the [observed] / [design-inference] / [verify] honesty tags live there. These are the grading authority; do not paraphrase their bands into this run.

Phase 1 — recon (subagent → returns a report, writes nothing)

Spawn one recon subagent. It fetches the actual SKILL.md (raw URL / local file, not memory of it — bioSkills moves fast) and returns a shared decomposition the four axis passes reuse, so nothing downstream re-fetches:

• Tool inventory — every external tool/package the skill names (Operability substrate).
• Claim/threshold inventory — load-bearing method choices, citations, CLI details, numeric thresholds (Traceability substrate).
• Candidate cardinal sin — the validity threat a Family-B referee would guard (Refereeability substrate).
• Fixture/data mentions — any dataset the skill uses or implies, and whether the domain has a small open-access benchmark (Assessability substrate).

Phase 2 — one research subagent per axis (parallel → each returns a graded report, writes nothing)

Spawn four subagents, one per rubric. Give each: the shared decomposition, the subject framing — "grade the best mirror we could build," not the external artifact as-shipped — and a pointer to its ONE rubric file. Each subagent reads its rubric, gathers the evidence that rubric's Scored-dimensions table names, and returns a grade per that rubric's bands, with evidence pointers, [verify] items it could not confirm, and gaps. Do not restate criteria in the prompt; the rubric is the spec.

Research protocol per axis (what to gather; the rubric says how to grade it):

• Operability (operability.md) — per tool: bioconda recipe? biocontainer/quay tag? container reference? LICENSE (open? copyleft?)? cross-platform? Grade the worst-case load-bearing tool.
• Assessability (assessability.md) — could we build a fixture-bound test for the mirror: a small, unrestricted dataset with known ground truth covering the skill's surface? Feasibility, not "does the skill ship one."
• Traceability (traceability.md) — lightweight recoverability triage: do the load-bearing claims / citations / CLI details resolve to real, ideally-OA primaries, or confabulate? Flag where a full /ingest-bioskill is needed to firm the grade.
• Refereeability (refereeability.md) — is the cardinal sin nameable, and can we construct a real Family-B referee (Critique plus an empirical Calibrate check) for the mirror?

House rule: subagents report, you write. No subagent writes files.

Phase 3 — assemble the scorecard (you write)

Write content/research/mold-eval/assessments/external-<skill-slug>.md:

• Header: subject, subject-type (external skill), source URL, date (today).
• The vector, up top: Operability <G> · Assessability <G> · Traceability <G> · Refereeability <G> — four letters, never a composite.
• Per axis: grade, evidence, unresolved [verify] items, gaps — each labeled [observed] / [design-inference].
• Work-list — the low axes are the actionable next steps (e.g. Traceability C → run /ingest-bioskill; Assessability D → no OA fixture, source one). This is the point of the card.

Keep the abstract rubrics untouched — the scorecard lives under assessments/, not in the rubric files.

Phase 4 — report (you)

Summarize: the four-letter vector, the sharpest strength and sharpest gap, the work-list, and any axis whose grade is [verify]-blocked (unconfirmed). Do not commit unless asked. List unresolved questions concisely.