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admet-reasoning

Interpretable ADMET analysis with mechanistic reasoning. Maps liabilities to structural causes and biological pathways. Based on CoTox (Park 2025) and DrugR (Liu 2026).

53

Quality

61%

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SecuritybySnyk

Passed

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tessl review fix ./backend/cli/skills/chemistry/admet-reasoning/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

68%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 clean, action-oriented skill body with executable commands, clear scope boundaries, and good file-level organization that correctly delegates detail to the bundled script. Its weaknesses are the missing validation/verification checkpoint for the batch workflow (which caps workflow clarity) and undocumented input/output formats for the CSV batch and JSON report.

Suggestions

Add a validation step to the batch workflow, e.g. 'After batch runs, verify the report row count matches the input and check the skipped-compounds list for unparseable SMILES before using results'.

Document the expected `compounds.csv` columns (e.g., a required `smiles` column) and show a trimmed example of the JSON report structure so outputs are predictable.

Consider moving the research citations (CoTox/DrugR details) into a short reference file or the script docstring to tighten the SKILL.md overview.

DimensionReasoningScore

Conciseness

The body is lean and task-focused — a short overview, tight 'When to Use'/'Do NOT use' lists, and three commands with no filler or explanation of concepts Claude already knows. The only trimmable padding is the research-justification block ('improved F1 from 0.37 to 0.66', 'improved scores 18×'), which is minor over-explanation. This matches 'efficient; minor instances of over-explanation' rather than the 3 anchor's 'some unnecessary explanation'.

4 / 5

Actionability

Three fully executable, copy-paste-ready bash commands (single molecule, batch CSV, targeted endpoints) plus an install command and a script table — matching the 5 anchor's 'copy-paste ready' quality. However, minor gaps remain: the required columns of `compounds.csv` are undocumented and the structure of the JSON report output is never shown, which fits the 4 anchor ('minor gaps') better than 5.

4 / 5

Workflow Clarity

The workflows are clearly presented (one unambiguous command each, with sequencing context via 'admet-prediction: run this first'), but the batch workflow (`--input compounds.csv` → `liability_report.csv`) has no validation or verification step — no check that SMILES parsed, no output row-count confirmation, no error-recovery guidance. Per the rubric, batch operations without validation cap workflow clarity at 3, taking precedence over the simple-skill exception.

3 / 5

Progressive Disclosure

The body is a well-organized overview (usage guidance, install, three workflows, script reference) that pushes implementation detail into the real, verified `scripts/reason_admet.py` — one level deep and clearly signaled via the Script Reference table. It is not the 5 anchor because the body runs ~75 lines (over the under-50 simple-skill threshold) and the model-output documentation (endpoint catalog, report schema) could arguably live in a separate reference file.

4 / 5

Total

15

/

20

Passed

Description

53%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.

A reasonably specific, domain-literate description that clearly states what the skill does, but it omits any when-to-use trigger guidance (capping completeness) and lacks natural trigger synonyms like 'toxicity'. It is mostly distinct from sibling skills, with minor overlap risk against admet-prediction since the description alone doesn't draw that boundary.

Suggestions

Append a trigger clause, e.g.: 'Use when interpreting ADMET/toxicity predictions for drug candidates, explaining why a liability was flagged, or planning structural fixes during lead optimization.'

Add natural synonyms users would actually say — 'toxicity', 'drug discovery', 'hERG', 'explain ADMET scores' — to improve trigger-term coverage.

Distinguish from the admet-prediction skill in the description itself, e.g., 'explains flagged ADMET liabilities (run after admet-prediction) rather than computing scores'.

DimensionReasoningScore

Specificity

The description names the domain ('Interpretable ADMET analysis with mechanistic reasoning') and one concrete action pattern ('Maps liabilities to structural causes and biological pathways'), but coverage is not comprehensive — suggested structural fixes, report generation, and endpoint targeting are absent. It sits at the '1-2 concrete actions, not comprehensive' anchor rather than the 'several specific actions, minor gaps' anchor above.

3 / 5

Completeness

The 'what' is clear (interpretable ADMET analysis mapping liabilities to structural causes and biological pathways), but there is no 'Use when...' clause or equivalent trigger guidance, which caps this dimension at 3 per the judging guidelines. It cannot score 4 without any 'when' component at all.

3 / 5

Trigger Term Quality

'ADMET' and 'liabilities' are relevant domain keywords a medicinal chemist would say, but common variations and synonyms are missing — 'toxicity', 'drug discovery', 'interpret ADMET scores', 'hERG', or 'explain predictions'. Matches 'some relevant keywords but missing common variations or synonyms' rather than the 'good coverage, a few natural terms missing' anchor.

3 / 5

Distinctiveness Conflict Risk

The mechanistic-reasoning framing carves a fairly clear niche, but 'ADMET analysis' overlaps with the closely related `admet-prediction` skill referenced in the body, and nothing in the description itself delineates the boundary (e.g., 'interpretation of predicted scores, not prediction'). This fits 'mostly distinct; minor overlap risk with closely related skills' — not the 5 anchor, which requires distinct triggers the description alone would fire on.

4 / 5

Total

13

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository
synthetic-sciences/openscience
Reviewed

Table of Contents

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