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Analyze check failures

analyze_check_failures
Read-only

Parses test, lint, typecheck, and build output into structured issues, identifies affected files, and provides guidance for creating a corrective patch.

Instructions

Parse test / lint / typecheck / build output into structured issues (file, line, code, message, priority), identify affected files, and return guidance for producing a corrective patch. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rawOutputNoRaw tool output to analyze when structured results are unavailable.
recentDiffNoThe most recently applied diff, for correlation.
projectPathYesAbsolute path to the project root.
checkResultsNoStructured results from run_project_checks.
taskDescriptionYesThe task being worked on (for context).
Behavior3/5

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

The annotation readOnlyHint: true already declares the tool is read-only, and the description redundantly states 'Read-only.' It adds some context about processing output and returning guidance, but does not disclose edge cases, failure modes, or any details beyond the annotation. Given the annotation covers the safety profile, a 3 is appropriate for the modest extra context.

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 primary action ('Parse') and packs in the output structure, affected files, and guidance. No wasted words; it earns every element.

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?

The tool has no output schema, so the description should hint at what it returns; it does ('structured issues' and 'guidance for a corrective patch'). However, it does not explain when to use rawOutput versus checkResults, which is a meaningful gap for a tool with two input modes. Still, the description is largely complete given the schema coverage.

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 all parameters have descriptive text. The tool description does not add parameter-specific details beyond the schema, and it only indirectly references rawOutput/checkResults via 'test / lint / typecheck / build output'. Since the schema already carries the full burden, a baseline 3 is warranted.

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 clearly states the verb 'Parse' and the resource 'test / lint / typecheck / build output', specifying the transformation into structured issues with fields (file, line, code, message, priority). This goes beyond the title by detailing the exact output and action, and distinguishes itself from siblings like run_project_checks (which runs checks) and generate_patch (which produces patches).

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 description implies usage when check output is available and needs parsing into issues, but it does not explicitly state when to use this tool versus alternatives like run_project_checks or create_change_plan. No exclusions or alternative references are provided, leaving usage context implicit rather than explicit.

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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