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BenAHammond

code-auditor-mcp

by BenAHammond

start_audit

Start a background audit job on a codebase to analyze code quality with configurable analyzers and severity levels. Returns a job ID for tracking progress.

Instructions

Start a background audit job. Returns immediately with a jobId. Poll audit_status until completed, then fetch pages with audit or audit_results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoFile or directory path to audit (defaults to current directory)./app
analyzersNoAnalyzers to run (default: solid, dry, documentation, react, data-access).
maxRetriesNoRetry attempts per shard for retryable failures (default: 1).
minSeverityNoMinimum severity level to report.warning
workerCountNoNumber of worker processes for shard execution (default: min(4, CPU-1)).
jobTimeoutMsNoMaximum wall time for the entire audit job (default 30m, env CODE_AUDITOR_JOB_TIMEOUT_MS, cap 4h). Aborts workers cooperatively then tears down.
maxPartitionsNoMaximum number of folder partitions for sharded audits (default: 4).
indexFunctionsNoIndex functions during audit (default: true).
maxFilesPerRunNoPer worker chunk: if more files match than this, the worker finishes one chunk and the parent queues the rest on another worker (optional).
retryBackoffMsNoBase retry backoff in milliseconds (default: 500).
shardTimeoutMsNoPer-shard timeout in milliseconds (default: 180000).
analyzerConfigsNoAnalyzer-specific configuration overrides.
generateCodeMapNoGenerate code map artifacts during audit (default: false).
partitionStrategyNoPartition mode: none | auto | top-level. auto shards when large source trees are detected.auto
shardSoftBudgetMsNoPer worker soft wall-clock budget; aborts in-process analysis cooperatively via AbortSignal so the parent can assign the next chunk to a fresh worker.
analyzerConcurrencyNoMax analyzers to run in parallel (default: 1).
partitionThresholdFilesNoMinimum discovered files before auto partitioning is enabled (default: 250).
Behavior3/5

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

No annotations are provided, so the description must disclose behavior. It correctly indicates asynchronous behavior (returns immediately) and the polling pattern. However, it does not mention potential side effects, resource usage, or required permissions. This leaves some ambiguity for a complex background job.

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 extremely concise—two sentences that efficiently convey the tool's purpose and the expected usage workflow. No unnecessary words or repetition.

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

Completeness3/5

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

Given the tool has 17 parameters, no output schema, and no annotations, the description could be more complete. It covers the async workflow but omits important context like what the audit results contain, how to interpret the jobId, or any error handling hints. The schema covers parameters, but the overall process is lightly documented.

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 all 17 parameters described in the input schema. The tool description adds no extra parameter context beyond the schema, which already explains default values, enums, and purpose. 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 clearly states the tool starts a background audit job, returns a jobId, and provides a workflow (poll audit_status, then fetch pages). This distinguishes it from sibling tools like audit, audit_status, etc., which focus on other aspects.

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

Usage Guidelines4/5

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

The description explicitly tells the agent to poll audit_status until completion and then fetch pages with audit or audit_results. However, it does not mention when not to use this tool or contrast with alternatives like a synchronous audit.

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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