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argot.check_hunk

Read-onlyIdempotent

Score a code hunk against your repository's learned style patterns to verify it fits the codebase's voice. Use for isolated snippets when no Git changeset is available.

Instructions

Score one supplied code hunk with Argot's fast fitted voice model. Use while drafting or for an isolated snippet when no Git changeset exists. Returns out_of_voice, score, threshold, rule, and concise evidence; it does not run semantic, architecture, integrity, or custom rules. For a real change, prefer check_changeset. Read-only; requires a fitted repository.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesRepo-relative path of the file the hunk belongs to. Its extension selects the language and that language's model (e.g. `.py`→Python, `.ts`→TypeScript, `.rs`→Rust); an unsupported extension yields no score.
file_sourceNoOptional: the full current text of the file. Provide it so argot can resolve callees against the surrounding code (more accurate when the hunk references names defined elsewhere in the file); omit it and the hunk is scored in isolation.
hunk_contentYesThe changed code to score — the added/edited lines, not the whole file. A few lines is enough; argot scores the hunk, not the file.
Behavior5/5

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

Adds behavioral context beyond annotations: return fields, exclusions, prerequisite (fitted repository). No contradiction with annotations.

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?

Three sentences: purpose, usage, output/exclusions. No wasted words, front-loaded with key information.

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?

Describes returns adequately given no output schema. Mentions limitations and prerequisites. Slightly lacking in return type detail, but sufficient for a simple read-only 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 coverage is 100% with detailed descriptions. The tool description does not add new info about parameters beyond what schema provides, so baseline 3.

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?

Clearly states the action (score), resource (code hunk), and model (fast fitted voice). Distinguishes from sibling check_changeset by noting preference for real changes.

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 says when to use: 'while drafting or for an isolated snippet when no Git changeset exists.' Also states exclusions (no semantic/integrity rules) and alternative (check_changeset).

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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