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estimate_audit

Estimate the mutant count and wall-clock time for an audit before running full mutation tests, guiding your decision to audit, downscope, or skip.

Instructions

Cheap pre-flight estimate of how big/long auditing a file will be, WITHOUT running the full mutation test cycle. Returns an approximate mutant count (for Rust, an exact count of the mutants cargo-mutants --list GENERATES — the audit scores fewer, excluding unviable ones as incompetent; a source heuristic for TS/JS/Python/PHP, labeled fidelity:"approx"). Set withTiming:true to also run the test suite once and estimate wall-clock time. Use this before audit_code_resilience to decide whether to audit now, scope down, or skip.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filePathYesPath to the source file to estimate, within the workspace. Example: "src/math.ts".
timeoutMsNoThe audit budget in milliseconds this estimate is GRADED against: budgetMs echoes it, and fitsBudget/recommendation compare the estimated time to it. Resolved exactly as audit_code_resilience resolves its own timeoutMs (same argument, config keys, and per-language defaults), so an estimate answers the question for the audit you would actually run. Default: 300000 (5 minutes). Must be <= 2147483647 (the largest delay a timer accepts). Example: 120000.
withTimingNoWhen true, run the test suite once to measure a baseline and estimate total wall-clock time (mutants × baseline / concurrency). Default false (count only, no test run).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteYes
basisYes
targetYes
mutantsYes
budgetMsNo
fidelityYes
languageYes
baselineMsNo
fitsBudgetNo
concurrencyNo
estimatedMsNo
optimisticMsNo
upperBoundMsNo
recommendationNo
timingConfidenceNo
Behavior5/5

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

With no annotations provided, the description fully discloses behavioral traits: it is "cheap" and does not run the full mutation cycle, returns language-specific counts with fidelity labels, and explains the withTiming option that runs the test suite once. It also notes that for Rust the count may overestimate the actual audit score due to excluding 'incompetent' mutants, which is valuable transparency.

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

Conciseness4/5

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

The description is information-dense with no filler, but it packs a lot of nuanced detail into a single paragraph, such as language-specific count behavior and fidelity labeling. While every sentence earns its place, the distribution could be improved slightly for readability; however, it remains concise and well-structured.

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

Completeness5/5

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

Given the tool's moderate complexity and the presence of a detailed output schema, the description covers all essential context: purpose, usage timing relative to audit_code_resilience, parameter effects, and return characteristics. With an output schema available, the description does not need to explain every return field, and it provides sufficient guidance for an agent to select and invoke the tool correctly.

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?

The input schema provides 100% coverage with detailed descriptions for all parameters, including timeoutMs and withTiming behavior. The tool description adds only a brief paraphrase (e.g., "Set withTiming:true to also run the test suite once"), which does not significantly exceed the schema's own explanations. Thus 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 clearly states the tool's function with a specific verb and resource: "estimate of how big/long auditing a file will be." It explicitly distinguishes itself from the sibling tool audit_code_resilience by noting it is a "pre-flight" step used before the actual audit, making its unique role unambiguous.

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?

Explicit usage guidance is provided: "Use this before audit_code_resilience to decide whether to audit now, scope down, or skip." This directly tells the agent when to invoke this tool relative to its key alternative, providing clear decision-making context.

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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