Jean — Molecular Biology & Genomics

crispr_analyze_screen

Read-only

Call HITS from a pooled CRISPR screen: per-guide read counts in, a gene-level Bayes factor and a precision/recall curve out.

Input Schema

Name	Required	Description
`_files`	No	The project: record references shaped like _subject. Their records become library documents a tool names in sequences/parts/document; a trace or alignment is found by file name.
`fdr_cut`	No	the false-discovery rate the hit list is cut at. A DISPLAY threshold read off the computed curve, not a parameter of the estimator.
`_subject`	No	The record to act on: exactly one of sequence, accession (+source), sample (an id from list_samples) or file ({name, text} or {name, base64}); record_index picks one record of several.
`min_reads`	No	drop a reagent whose SUMMED control count is below this (upstream's -m). Applied after the pseudocount, exactly as upstream applies it.
`read_counts`	Yes	the count table: a header line, then one row per reagent — identifier, gene, then one column per sequenced sample. Tab- or comma-separated. Counts may be written as decimals, as upstream's own files are.
`pseudo_count`	No	added to every count before normalising to 10,000,000 reads per column. Advanced.
`sample_columns`	No	which sample column names to score. Leave empty to score every column that is not a control.
`control_columns`	Yes	the T0 / plasmid column NAMES, exactly as the header spells them. Summed before the fold change, so a two-replicate T0 is one control and not two.
`essential_genes`	Yes	reference ESSENTIAL gene symbols, one per line (extra columns ignored). BAGEL2's CEGv2 is the usual choice; the editor panel ships it and the mouse set beside it.
`equalise_replicates`	No	scale every Bayes factor as if the screen had this many replicates (upstream's -p), 0 to leave it off. A BF is a SUM over replicates, so two screens of different replicate counts are not comparable until this is set. Advanced.
`non_essential_genes`	Yes	reference NON-ESSENTIAL gene symbols, one per line. BAGEL2's NEGv1 is the usual choice.

Output Schema

Name	Required	Description
`fit`	Yes	the fitted line the Bayes factor is scored against: slope, intercept and the fold-change window
`hits`	Yes	genes at or above the Bayes factor the FDR cut lands on
`curve`	Yes	the precision/recall curve, one row per gene
`genes`	Yes	every gene with its Bayes factor, standard deviation and observation count, ranked
`hitBf`	Yes	the Bayes factor the cut lands on (0 when nothing clears the FDR)
`training`	Yes	reference essential and non-essential genes FOUND in this library, against the number supplied — the check that the symbols match

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 20, 2026

TDQS

A3.6/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already establish that this is a read-only, non-destructive, non-open-world analysis. The description adds useful context that it transforms per-guide read counts into a gene-level Bayes factor and a precision/recall curve, but it does not discuss assumptions, computational cost, or reference-set requirements beyond the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The definition is a single front-loaded sentence with no filler. The colon cleanly separates the tool action from the input/output summary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the rich input schema and the presence of an output schema, the one-sentence description is enough to understand the tool's high-level role. It leaves workflow details and required reference gene sets to the schema, which is acceptable here.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the schema already documents all 11 parameters, including control_columns, gene reference lists, fdr_cut, and advanced options. The description frames the main input and output but adds no parameter-specific meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource: 'Call HITS from a pooled CRISPR screen,' and it clarifies the input and output data flow. It does not explicitly distinguish this from closely related CRISPR siblings such as crispr_score_deephf, crispr_score_deepspcas9, or screen_guides.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The pooled-screen context implies when the tool is appropriate, but it gives no explicit when-to-use guidance, prerequisites, or alternatives. It does not state when another CRISPR scoring tool should be chosen instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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