brain_fabrication_audit

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

With no annotations provided, the description carries the behavioral disclosure burden. It clearly labels the operation as 'read-only' and 'static,' indicating no side effects. It also discloses the limitation that findings are a 'signal, not proof,' which is important for correct interpretation. It does not describe internal behavior like rate limits or exact scanning methodology, but this is sufficient for a scan tool.

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 concise, using only two sentences to convey purpose, scope, usage guidance, and parameter override. It is front-loaded with the verb and resource, making it easy to quickly grasp. No filler or redundant information.

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?

The tool has no output schema, so the description should ideally clarify what the tool returns (e.g., list of findings, severity, file paths). While it mentions 'findings' and 'certifying REAL/ABSENT,' it does not describe the return format or pagination. Given the moderate complexity and lack of output schema, the description is serviceable but leaves room for ambiguity about the exact output structure.

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 0%, so the description must compensate. It does so by explaining that the `dirs` parameter 'overrides the configured SYSTEM_BRAIN_FABRICATION_DIRS list for this call,' which gives meaningful context beyond the raw schema. The description does not explain element formatting or constraints, but the single-parameter scope is adequately addressed.

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 performs a 'read-only static scan' for 'fabricated-core leaves' with a specific definition (Math.random()-fed confidence/accuracy/score/decision values). It also scopes the scan to 'configured engine directories' and distinguishes itself from sibling tools by focusing on fabrication auditing rather than deployments, backlog, or architecture.

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 gives practical usage context: it is a 'signal, not proof' and directs users to 'verify each finding against stub-detection-audit before certifying REAL/ABSENT.' It also explains how the `dirs` parameter overrides the default directory list. However, it does not explicitly contrast with sibling tools or state when not to use the tool.

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