depmap

Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles. Use for identifying cancer-specific vulnerabilities, synthetic lethal interactions, and validating oncology drug targets.

Quality

75%

Does it follow best practices?

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Passed

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Quality

Content

57%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.

The body delivers strong, executable code and a clear data-file reference table, but it is padded with concepts Claude already knows, has abstract workflows lacking validation, and fails to surface the existing dependency_analysis.md reference. The main levers for improvement are trimming redundant explanation and wiring up the reference file.

Suggestions

Link references/dependency_analysis.md from the body (e.g., 'See [dependency_analysis.md](references/dependency_analysis.md) for score interpretation, selectivity scoring, and synthetic-lethality/PRISM details') and move the duplicated synthetic-lethality and PRISM code there instead of inlining it.

Replace the placeholder 'https://figshare.com/ndownloader/files/...' URL with the concrete current download path or a clearly-labeled versioned pointer so the download example is runnable.

Tighten the Overview and Best Practices sections by removing restatements of what DepMap/CRISPR is and basic programming concepts Claude already knows; keep only DepMap-specific guidance.

Add explicit validation checkpoints to the workflows (e.g., check row/column counts after loading a file, confirm the target gene exists before scoring, apply FDR correction as a stated step in the synthetic-lethality workflow).

Dimension	Reasoning	Score
Conciseness	Mostly efficient with concrete code, but the Overview re-explains what DepMap is, the 'DepMap data is essential for' list and Core Concepts table restate concepts Claude already knows, and Best Practices prose could be tightened — matching the 'mostly efficient but could be tightened' anchor rather than the lean score-4 example.	3 / 5
Actionability	Provides several copy-paste-ready Python functions (dependency lookup, downloads, selective-dependency filtering, biomarker analysis, co-essentiality), but the FILES dict uses a placeholder figshare URL and example usage is commented out, leaving minor gaps short of fully executable.	4 / 5
Workflow Clarity	Three workflows give a numbered sequence, but steps are abstract ('Filter cell lines', 'Compute mean gene effect') with no validation checkpoints; for these batch/genome-wide analyses the missing validation caps workflow clarity at 3 per the batch-operations guideline.	3 / 5
Progressive Disclosure	Section structure is reasonable, but a substantial references/dependency_analysis.md bundle exists and is never linked from the body, while synthetic-lethality and PRISM content is duplicated inline instead of pointed to the reference — 'references present but not clearly signaled; content that should be separate is inline'.	3 / 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 clearly states both the capabilities and the use-conditions of the skill with concrete domain triggers. It is only slightly short of fully comprehensive trigger-term coverage (e.g., file extensions or additional synonyms).

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'gene dependency scores (CRISPR Chronos)', 'drug sensitivity data', 'gene effect profiles', 'identifying cancer-specific vulnerabilities', 'synthetic lethal interactions', and 'validating oncology drug targets' — giving comprehensive coverage rather than the 1-2 actions of a score-4 anchor.	5 / 5
Completeness	Explicitly answers both 'what' (query DepMap for dependency, drug sensitivity, and gene effect data) and 'when' ('Use for identifying cancer-specific vulnerabilities, synthetic lethal interactions, and validating oncology drug targets') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Strong natural domain terms ('DepMap', 'cancer cell line', 'gene dependency scores', 'CRISPR Chronos', 'synthetic lethal interactions', 'oncology drug targets') that a user would say, but it stops short of the synonym/file-extension-level comprehensiveness of the score-5 anchor.	4 / 5
Distinctiveness Conflict Risk	Occupies a clear niche (DepMap oncology dependency data) with distinct triggers and 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: K-Dense-AI/scientific-agent-skills
Path: skills/depmap/SKILL.md
Commit: b2a92ba

Reviewed: 3 days ago

Table of Contents

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