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crispr_quantify_edits

Read-only

Quantify a CRISPR edit from a pair of Sanger traces — how much of the population was edited, what the indel spectrum looks like, and how well the model fits. Synthego ICE: the CONTROL trace gives the unedited sequence, the EDITED trace is decomposed into a mixture of proposed indels around each guide's cut, and the abundances are fitted. Answers the question a screen cannot: not whether a guide is good, but what it actually did to these cells.

Input Schema

NameRequiredDescriptionDefault
donorNooptional HDR donor / ssODN. Given one, ICE also proposes the recombination outcome and reports an HDR percentage; left empty there is no HDR arm rather than a zero.
_filesNoThe 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.
editedYesthe EDITED trace, by file name or id.
guidesYesthe guide spacers, RNA accepted. Each is located in the CONTROL on either strand, so the cut sites come from the data rather than from a coordinate you supply.
controlYesthe UNEDITED trace, by file name or id — it supplies the reference the edited read is decomposed against.
_subjectNoThe 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.
base_editingNoalso fit every single-base change on the PAM-distal side of each cut, for a base editor. Left false, the scores stay comparable with published ICE numbers, which the extra proposals would move. Advanced.
indel_max_sizeNolargest single-cut indel modeled either side of the cut — ICE's own CLI default is 20. In bp. Advanced.

Output Schema

NameRequiredDescriptionDefault
iceDYesICE-D, an independent discordance-based read on the same trace — a second opinion rather than a restatement
checksYesTIDE once per guide and tracy's breakpoint call on the same pair, reported beside ICE and never averaged into it; tracy's `status` says whether it agrees with ICE's top sizes
hdrPctYesthe HDR percentage, when a `donor` was given
reportYesthe whole result, including ICE's own notes and warnings
iceScoreYesthe headline ICE score: the edited fraction of the population, 0-100
perGuideYeseach guide's own answer: its cut (control base, from 1), the share edited there, its indel spectrum at that cut alone, and the alleles edited at it and another cut
rSquaredYeshow well the fitted mixture explains the edited trace. A high ICE score with a poor fit is not a result, and this is the number that says so
spectrumYesthe indel-size histogram ICE publishes, every size from -2x to +1x `indel_max_size` INCLUDING the zeros, so the spectrum's shape is visible and not only its peaks
baseEditsYeswith `base_editing`, each fitted substitution (protospacer position, control base, change, share, refit interval), the range of the pool carrying any, and the notes on phasing and near-cut calls; null otherwise
inseparableYesgroups of reported alleles this trace cannot tell apart (their expected traces correlate above a variance inflation factor of 5), each with its summed share and 95% interval; the split inside a group is not measured
contributionsYeseach proposed edit with its relative abundance, most abundant first
knockoutScoreYesthe fraction carrying a frameshift or a 21+ bp indel — the number a knockout experiment is actually asking for, which is NOT the same as the edit fraction

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedOutput schema / properties / hdrPct / x-unit
      Added value: +"%"
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly/ non-destructive/closed-world, so the safety profile is covered; the description goes further and discloses non-obvious behavior: an absent donor yields 'no HDR arm rather than a zero', and base_editing would shift scores away from published ICE comparability. It does not discuss runtime cost, failure modes on poor traces, or what a failed fit looks like, which keeps it short of a 5.

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

Conciseness4/5

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

One front-loaded paragraph: the action and outputs come first, the ICE mechanics second, the sibling contrast last. Roughly 90 words with no redundant sentences. The rhetorical closer ('Answers the question a screen cannot') is vivid but arguably costs a little space given the density of the mechanics sentences.

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?

With an output schema present, return values needn't be explained, and the description plus schema together cover all 8 parameters, the HDR branch, and the base-editor variant. The only omissions are the generic project-record plumbing (_subject/_files), which the schema handles, and any mention of trace-quality prerequisites — minor for a read-only analysis tool.

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%, so every parameter including donor, base_editing, indel_max_size and the _subject/_files plumbing is documented in structured form — baseline 3. The description adds interpretive framing (guides located on either strand, cut sites from data, HDR arm semantics) but largely restates what the schema already says rather than adding new parameter-level meaning.

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

Purpose5/5

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

States a specific verb (quantify) and resource (a CRISPR edit from a pair of Sanger traces) and enumerates the three outputs: edit fraction, indel spectrum, model fit. It then names and contrasts the sibling class it is not — screens ('not whether a guide is good, but what it actually did to these cells') — so an agent can separate it from crispr_analyze_screen and screen_guides without opening a schema.

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

Usage Guidelines4/5

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

Gives clear context: a CONTROL trace supplies the unedited reference, an EDITED trace is decomposed against it, and guides are located in the control so cut sites are derived from data. The screen-vs-measure framing is an effective when-to-use signal. It stops short of naming the nearest alternatives (tide_quantify_indels, quantify_base_editing, detect_trace_indel) or stating exclusions, so it is clear but not fully routing.

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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