chembl-database

Query the ChEMBL database for bioactive molecules, drug targets, bioactivity data, approved drugs, and chemical structures. Use when the user asks about compounds, targets, IC50/Ki values, drug mechanisms, or structure searches.

Quality

73%

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Quality

Content

53%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.

Well-structured and concrete, but undermined by malformed code fences (not copy-paste ready), an inlined endpoint list that duplicates the reference file, and missing validation checkpoints for batch/pagination operations.

Suggestions

Fix the malformed code blocks: replace `bash ...` inline-code runs with proper triple-backtick fenced bash blocks so commands are copy-paste executable.

Move the 'Full subcommand list' (lines 226-250) into references/api_endpoints.md and link to it from SKILL.md, keeping only the 'Key subcommands at a glance' summary inline.

Add validation/feedback steps to batch and pagination workflows (e.g., check status result before proceeding, verify returned count against page_meta.total_count, handle empty/error responses).

Dimension	Reasoning	Score
Conciseness	Mostly efficient with no concept padding, but the inlined 25-line 'Full subcommand list' duplicates content that belongs in the existing reference file, and the broken code-fence formatting reduces readability.	3 / 5
Actionability	Commands are concrete, but most code blocks are malformed (use `bash` inline-code fences instead of triple-backtick blocks), so they are not copy-paste executable as written.	3 / 5
Workflow Clarity	An 8-step workflow with an initial status check exists, but batch fetch and pagination of large result sets lack validation/feedback loops, capping this at 3 per the rubric.	3 / 5
Progressive Disclosure	Good section structure with a clearly signaled, verified reference link to references/api_endpoints.md; the only gap is the inlined full-subcommand list that should live in the reference file.	4 / 5
	Total	13 / 20 Passed

Description

92%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 strong, specific description that cleanly answers what the skill does and when to use it, with good trigger terms and a distinct niche. Only minor gap is synonym/extension coverage in trigger terms.

Dimension	Reasoning	Score
Specificity	Names multiple concrete capabilities ('bioactive molecules, drug targets, bioactivity data, approved drugs, and chemical structures'), giving comprehensive coverage rather than just 1-2 actions.	5 / 5
Completeness	Explicitly answers both 'what' (query ChEMBL for the listed data) and 'when' ('Use when the user asks about...') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Good natural trigger terms ('compounds, targets, IC50/Ki values, drug mechanisms, or structure searches'), but missing some synonyms and extensions that anchor 5 requires.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche (the ChEMBL database) with domain-specific triggers, giving minimal overlap risk with other skills.	5 / 5
	Total	19 / 20 Passed

Validation

100%

Warnings & errors only

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: google-deepmind/science-skills
Path: skills/chembl_database/SKILL.md
Commit: 6883275

Reviewed: 4 days ago

Table of Contents

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