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Get raw evidence for your own judgment

extract_evidence

Return every pattern match with the quote and rule that fired plus unmatched turns. Review each candidate yourself to catch sarcasm and unpatterned behavior.

Instructions

Return every pattern match the instrument found, with the quote and the rule that fired, plus the turns where nothing matched. Use this when the reading matters more than the number: you confirm or reject each candidate yourself, catching sarcasm and quoted speech that a word list scores wrong, and catching behavior in the unmatched turns that no pattern covers. This is the tool for producing a defensible qualitative summary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metaNoLabels carried into the report and used for cohort grouping, e.g. {"cohort": "spring-2026", "site": "Cleveland"}.
formatNoOverride format auto-detection.
indicatorsNo
transcriptNoRaw transcript text. Supply this or transcript_path.
speaker_aliasesNoRename speakers after parsing, e.g. {"Speaker 1": "Participant A"}. Use this to de-identify before results are shared.
transcript_pathNoPath to a transcript file. Supply this or transcript.
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the tool returns all pattern matches with quote and rule, and includes non-matching turns, indicating a transparent read-only behavior. However, it doesn't mention output size limits or performance considerations, which could affect agents expecting large datasets.

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?

The three sentences are well organized: action first, then use case, then a summary positioning statement. While slightly verbose for a tool description, each sentence contributes meaningful guidance without waste.

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?

Despite having no output schema, the description conveys the essential output elements (quote, rule, unmatched turns). It does not explicitly state that a prior scoring run (or 'instrument') is required, but the phrase 'the instrument found' implies it; this is a minor gap given the tool's complexity.

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 already provides descriptions for 5 of 6 parameters (83% coverage), so the baseline is 3. The description adds no parameter-specific detail beyond what the schema offers; for example, it doesn't explain how the 'indicators' parameter filters the evidence.

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?

The description uses a specific verb ('Return') and a precise object: 'every pattern match the instrument found, with the quote and the rule that fired, plus the turns where nothing matched.' This clearly distinguishes it from sibling scoring tools like score_conversation by emphasizing raw evidence over numeric output.

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

Usage Guidelines5/5

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

Explicitly states when to use it: 'when the reading matters more than the number' and contrasts with 'a word list scores wrong,' implicitly naming the alternative approach. It further frames itself as 'the tool for producing a defensible qualitative summary,' giving clear guidance for selection.

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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