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extract_facts

Extract current implementation facts from non-documentation files to compare documentation claims with the real source code, enabling drift detection.

Instructions

Extract current implementation facts from discovered non-documentation files.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audit_idYesIdentifier returned by create_audit.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

Annotations indicate readOnlyHint=false, meaning the operation may have side effects, but the description only says 'Extract', which could imply a read-only action. It does not disclose that results may be stored or that an audit must exist (though the schema parameter does). It adds some useful context about the input source ('non-documentation files') but does not elaborate on write behavior or side effects, which is a moderate transparency level given the annotation bar.

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 description is a single, well-structured sentence that front-loads the action and resource. Every word contributes meaning, with no redundant or filler content. It is highly concise and readable.

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?

For a tool with one parameter and an output schema, the description is largely complete. It clarifies the source of input files ('discovered non-documentation files') and ties it to the audit context via the parameter schema. It could be improved by explicitly stating the relationship to 'discover_sources' and what happens with the extracted facts (e.g., stored in the audit), but the presence of an output schema reduces the need to explain return values.

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% because the only parameter, 'audit_id', is described as 'Identifier returned by create_audit.' This fully explains the parameter's meaning and origin. The tool description itself adds no additional parameter information, so the baseline of 3 is appropriate.

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 ('Extract') and clearly identifies the resource ('current implementation facts') and the source scope ('discovered non-documentation files'). It distinguishes itself from the sibling tool 'extract_claims' by explicitly targeting non-documentation files, which clearly differentiates the two.

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 phrase 'from discovered non-documentation files' implies that this tool should be used after a discovery step, but it does not explicitly say when to use it compared to alternatives like 'extract_claims'. There is no explicit 'when-not' guidance or naming of alternative tools, so usage context is only implied, not fully specified.

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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