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tooluniverse-crispr-screen-analysis

Analyze CRISPR-Cas9 genetic screens — MAGeCK gene-level scores, sgRNA count QC, replicate correlation, hit prioritization, and pathway GSEA on screen output. Use for genome-wide essentiality screens, synthetic-lethality discovery, dropout vs positive-selection screen analysis, target identification, and resistance-screen interpretation. Includes screen-QC and statistical thresholds.

Quality

85%

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SecuritybySnyk

Low

Low-risk findings worth noting

The canonical home for this skill is tooluniverse-crispr-screen-analysis in mims-harvard/ToolUniverse

SKILL.md
Quality
Evals
Security

Quality

Content

71%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 domain-rich, well-sequenced analysis skill with concrete thresholds, real tool parameters, and thoughtful QC/interpretation guidance. Its main defects are dangling references — five See Also files and a .gmt bundle that are not in the bundle — and a Quick Start built on undefined helper functions, plus minor redundant introductory prose.

Suggestions

Resolve the dangling references: either add ANALYSIS_DETAILS.md, USE_CASES.md, EXAMPLES.md, QUICK_START.md, FALLBACK_PATCH.md and the Reactome .gmt file to the bundle, or remove them from See Also and inline the essential parts (especially the definitions behind the Quick Start's helper functions).

Make the Quick Start executable: the eight called functions (load_sgrna_counts, create_design_matrix, filter_low_count_sgrnas, normalize_counts, calculate_lfc, mageck_gene_scoring, enrich_essential_genes, prioritize_drug_targets, generate_crispr_report) are undefined anywhere in the bundle — ship them in scripts/ or replace the example with the real ToolUniverse calls.

Trim redundancy for conciseness: delete the 'Comprehensive skill for analyzing...' paragraph and the 'CRISPR screens enable genome-wide functional genomics...' sentence, and merge the Overview bullet list into the Core Workflow phase headings it duplicates.

DimensionReasoningScore

Conciseness

The body is dense with earned content — thresholds ("LFC < -1.0", "delta-LFC > 1.5", "recovers >~0.8"), tool names with exact parameters, and evidence grades. Minor trimmable padding exists: the opening "Comprehensive skill for analyzing..." paragraph and the "CRISPR screens enable genome-wide functional genomics..." sentence restate the description and domain background Claude already knows. Above 3 (mostly efficient), below 5 (not every token earns its place — Overview duplicates the phase list and the intro duplicates the frontmatter).

4 / 5

Actionability

Mostly concrete: a runnable command ("tu run read_executed_notebook '{...}'"), tool calls with exact parameter shapes ("identifiers newline-separated, page_size"; "genes as array"), a working bundle import ("from reference_gene_sets import core_essential, nonessential, recovery_rate"), and numeric defaults throughout. The gap: the Quick Start calls eight helper functions (load_sgrna_counts, mageck_gene_scoring, etc.) that are not defined anywhere in the bundle, making that example non-executable as written. That keeps it below 5; the rest of the guidance stays above the 3 anchor's "pseudocode and missing key details" level.

4 / 5

Workflow Clarity

A clearly sequenced 8-phase workflow gated by an explicit pre-check (RULE ZERO), with QC checkpoints (Gini coefficient, zero-count, library-size checks in Phase 2; core-essential recovery rate as a screen-quality gate) and a genuine feedback loop ("If you get rho ~ 0.6+ you are probably at gene level; drop to per-sgRNA CPM pairs"). Below 5 because failure handling is mostly "report recommendations" rather than explicit validate-fix-retry loops at each phase. This is a read-only analysis skill, so the destructive/batch cap does not apply.

4 / 5

Progressive Disclosure

In-body structure is good (well-sectioned phases, interpretation framework, conventions), and the scripts/ reference is real and accurately described (reference_gene_sets.py with CEGv2/NEGv1 matches the listing). However, the See Also section points to five files (ANALYSIS_DETAILS.md, USE_CASES.md, EXAMPLES.md, QUICK_START.md, FALLBACK_PATCH.md) and a ".gmt bundle" that do not exist in the bundle, so the promised detailed layer is inaccessible and ~200 lines of phase detail remain inlined in SKILL.md. Between the 2 anchor (references fail/buried) and 3 anchor (some structure, references present but problematic); the solid in-body organization and the real scripts/ files keep it at 3.

3 / 5

Total

15

/

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 description that names a clear niche, enumerates concrete analytical capabilities, and includes an explicit multi-trigger "Use for..." clause. Its only weakness is slightly incomplete natural-synonym coverage of common user phrasings (pooled/knockout/fitness screens, file formats).

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions with comprehensive coverage: "MAGeCK gene-level scores, sgRNA count QC, replicate correlation, hit prioritization, and pathway GSEA on screen output" plus "screen-QC and statistical thresholds". These are concrete, named analytical capabilities rather than generic verbs.

5 / 5

Completeness

Explicitly answers both questions: the first sentence states what it does ("Analyze CRISPR-Cas9 genetic screens — ...") and the second gives an explicit trigger clause ("Use for genome-wide essentiality screens, synthetic-lethality discovery, dropout vs positive-selection screen analysis, target identification, and resistance-screen interpretation"). Not below 5 because both what and when are explicit and concrete; not a 4 because the when-clause enumerates specific trigger phrases rather than a vague condition.

5 / 5

Trigger Term Quality

Good natural-term coverage: "CRISPR-Cas9", "genome-wide essentiality screens", "synthetic-lethality discovery", "dropout vs positive-selection screen", "resistance-screen interpretation". A few natural variants users would say are missing (e.g., "pooled screen", "knockout screen", "fitness screen", MAGeCK output file extensions), so it sits between the 4 and 5 anchors but closer to 4.

4 / 5

Distinctiveness Conflict Risk

Clear niche with distinct triggers: CRISPR-Cas9 screen analysis with MAGeCK/sgRNA/DepMap-adjacent vocabulary is unlikely to be confused with general bioinformatics or expression-analysis skills. Not below 5 because the trigger domain is narrow and the vocabulary (sgRNA, dropout screens, synthetic lethality) is unmistakable.

5 / 5

Total

19

/

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

mims-harvard/ToolUniverse

Path

plugins/tooluniverse/skills/tooluniverse-crispr-screen-analysis/SKILL.md

Reviewed

Table of Contents

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