argot.check_changeset

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

Annotations declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral details: 'it does not fit, mute, edit files, or update the last-check cache; requires a fitted repository.' This goes beyond annotations and clarifies side effects and prerequisites.

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

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

The description is two sentences plus a brief note, all front-loaded with the most important information. Every sentence adds value: purpose, usage context, return type, and behavioral constraints. No wasted or redundant words.

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

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

With 5 parameters all documented in schema and no output schema, the description covers the return value ('stable check JSON, including findings, evidence, suppressions, and result counts') and a critical prerequisite ('requires a fitted repository'). This is complete for an agent to understand input/output and constraints.

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

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

Schema description coverage is 100%, so each parameter already has a description. The tool description adds no additional parameter semantics beyond what the schema provides. Baseline 3 is appropriate since the schema does the work.

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

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

The description clearly states the tool runs the complete detector pipeline over one changeset and returns check JSON. The verb 'check' is specific, and the phrase 'complete configured detector pipeline' and reference to CLI distinguish it from sibling tools like check_hunk.

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

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

The description explicitly says 'Use this after editing when you need the same voice, semantic, architecture, integrity, and custom-rule findings as the CLI.' It also clarifies what it does not do (fit, mute, edit files, update cache), providing when-not-to-use guidance. It does not name alternatives directly but the context and tone imply it's for full pipeline checks.

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