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Request Rule

request_rule
Destructive

Request a new Code Auditor rule. Call lookup_rule or explain_symptom first to confirm no existing rule covers it. Provide a minimal example that should be flagged and a corrected example that should not. Reduce both to the smallest code that shows the difference, and remove secrets and proprietary identifiers. Returns a receipt id.

Input Schema

NameRequiredDescriptionDefault
titleYes
signalYes
symptomYes
languagesYes
toolVersionNo
cleanExampleYes
firingExampleYes

Output Schema

NameRequiredDescriptionDefault
idYes
duplicateSubmissionYes
existingRuleMatchesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare the risky profile (destructiveHint=true, non-idempotent, not read-only), so the description is not the sole carrier here. It adds useful context — the submission hygiene requirement to minimize examples and strip secrets/proprietary identifiers, plus the return value ('a receipt id') — but never explains what the destructive write actually affects, whether the request persists, or what review/approval follows. Adequate but with a clear gap given a destructive, non-idempotent operation.

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?

Four short sentences, front-loaded with purpose, then precondition, then content requirements, then return value. No filler and no repetition of schema constraints.

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?

The output schema covers the return shape (and the receipt id is mentioned anyway), so return values are handled. However, for a destructive, non-idempotent submission tool with six required parameters and no schema descriptions, the definition omits what happens after submission, whether the request is persisted or reviewable, and any permission requirements — the remaining gaps an agent would want before committing a write.

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 0% across 7 parameters, so the schema documents names and constraints only. The description meaningfully explains two of them ('a minimal example that should be flagged' and 'a corrected example that should not', mapping to firingExample/cleanExample), but leaves title, symptom, signal, languages, and toolVersion with no meaning beyond their names and length limits. Partial compensation, not full.

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?

States a specific verb and resource ('Request a new Code Auditor rule') and immediately distinguishes itself from siblings by naming lookup_rule and explain_symptom as the discovery tools that precede it. An agent can tell this apart from the read-only lookup tools without opening any schema.

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?

Gives an explicit precondition ('Call lookup_rule or explain_symptom first to confirm no existing rule covers it'), which doubles as a when-not-to-use rule: if an existing rule covers the symptom, don't call this. The alternatives are named directly rather than implied.

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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