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boltz-small-molecule-screen

Screen existing small-molecule libraries with Boltz. Use when docking, scoring, or ranking a supplied SMILES or compound library against a target; also returns free Tier-1 ADME/ADMET (solubility, permeability, lipophilicity/logD) per molecule. Not for de novo molecule design, one-off docking, or ADME on bare SMILES with no target (use boltz-small-molecule-adme).

75

Quality

92%

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SKILL.md
Quality
Evals
Security

Quality

Content

85%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A strong, highly actionable skill body: executable commands with all flags, a sequenced workflow with real validation gates (estimate-cost + explicit confirmation before spend) and error-recovery paths, and a clean two-file reference split that is clearly signaled and one level deep. The one weakness is redundancy — the multi-runtime background-download and heartbeat instructions are restated across the workflow, the command comments, and the Always Do This bullets, which inflates token cost without adding new information.

Suggestions

State the background/non-blocking download guidance (Claude Code run_in_background vs Codex foreground with yield_time_ms=1000, no &/nohup) once — either in workflow step 6 or as a single Always Do This bullet — and reference it from the Command Pattern comment instead of repeating the full text in all three places.

Merge the heartbeat bullet into workflow step 6 (or vice versa): the cadence table (under 100 -> 1-2 min, 100-1,000 -> 5 min, over 1,000 -> 15 min) and the 'report job ID, run name, output directory, next-check cadence' instruction each appear twice.

Consolidate the payload field-name guidance: 'Payload keys are molecules, target, molecule_filters — the API body field names...' in the Command Pattern section and the first two Always Do This bullets restate the same API-body-vs-CLI-flag rule three times; one statement plus the api.md pointer suffices.

DimensionReasoningScore

Conciseness

The body is dense and operational with no padding explaining known concepts, but the background-download guidance is repeated three times — in workflow step 6 ('In Claude Code, use Bash with run_in_background: true. In Codex, run download-results as a foreground shell command with yield_time_ms: 1000...'), in the Command Pattern comments ('Claude Code: Bash with run_in_background=true. Codex: foreground shell command with yield_time_ms=1000'), and in two Always Do This bullets ('Prefer the agent runtime's background/non-blocking command mode for download-results... Do not append & or use nohup in Codex'), with the heartbeat cadence rules (1-2/5/15 min) and the 'report job ID, run name, output directory' instruction each also stated twice. This is real tightening work, matching 'mostly efficient but could be tightened' rather than the 'minor instances' of a 4.

3 / 5

Actionability

Fully executable copy-paste commands are provided for every phase — 'boltz-api small-molecule:library-screen estimate-cost --input @yaml:///absolute/path/payload.yaml', 'start' with '--idempotency-key ... --raw-output --transform id', and 'download-results --id ... --name ... --root-dir ... --poll-interval-seconds 30' — with placeholder substitution documented in comments and concrete output paths ('-> /absolute/path/boltz-experiments/<run-name>/results/<pres_*>/...'). Specific examples cover the common cases, matching the top anchor.

5 / 5

Workflow Clarity

Steps 1-7 are clearly sequenced with explicit validation checkpoints and error-recovery loops: estimate-cost with 'wait for explicit confirmation' gates the money-spending batch submit, the job ID is captured before download, auth/sandbox failures route to 'boltz-cli-setup ... before retrying', and a failed download is recovered by re-running with the same '--name' and '--root-dir' so '.boltz-run.json' resumes. The batch-operation validation cap does not apply because a cost/confirmation gate is explicitly present.

5 / 5

Progressive Disclosure

SKILL.md is an overview with exactly two well-signaled, one-level-deep references, both verified to exist and to hold the bulk detail: 'Read [references/api.md](references/api.md) for the molecules, target, and molecule_filters shapes' (227-line payload reference) and 'Read [references/results.md](references/results.md) for output layout, metrics, ADME, and filtered-input accounting'. The split is appropriate — payload and output detail live in the bundle, operational guidance stays inline — and navigation is easy.

5 / 5

Total

18

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

An exemplary description: it states concrete capabilities with enumerated ADME subfields, gives an explicit 'Use when' trigger clause with natural domain terms and synonyms, and closes with explicit negative boundaries that route de novo design and bare-SMILES ADME requests to the sibling skill. Third-person voice throughout, concise, no fluff or over-claims.

DimensionReasoningScore

Specificity

The description lists multiple concrete capabilities with comprehensive coverage of the skill's scope: 'Screen existing small-molecule libraries with Boltz', 'docking, scoring, or ranking a supplied SMILES or compound library against a target', and 'returns free Tier-1 ADME/ADMET (solubility, permeability, lipophilicity/logD) per molecule'. Not a 4: the ADME subfields are enumerated and the exclusions are explicit, so there are no minor coverage gaps — it exceeds the 'several specific actions' bar.

5 / 5

Completeness

It explicitly answers both questions: what it does ('Screen existing small-molecule libraries with Boltz ... also returns free Tier-1 ADME/ADMET ... per molecule') and when to use it ('Use when docking, scoring, or ranking a supplied SMILES or compound library against a target'), with concrete trigger phrases. Not a 4: the 'when' clause is explicit and specific, not merely present.

5 / 5

Trigger Term Quality

Natural user phrasing is comprehensively covered including synonyms: 'docking', 'scoring', 'ranking', 'SMILES', 'compound library', 'ADME/ADMET' (both forms), 'solubility', 'permeability', 'lipophilicity/logD', and 'de novo molecule design' — exactly the terms a medchem user would say when they need this skill. Not a 4: no common domain synonym or format term is missing.

5 / 5

Distinctiveness Conflict Risk

It occupies a clear niche and actively disambiguates from the nearest sibling: 'Not for de novo molecule design, one-off docking, or ADME on bare SMILES with no target (use boltz-small-molecule-adme)'. Not a 4: conflict risk is explicitly routed away from the overlapping skill rather than merely reduced.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
openai/plugins
Reviewed

Table of Contents

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