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test_ruleset

Read-only

Run a ruleset against fixture documents with expectations — codes that must fire, exact counts, or a clean lint — and report pass/fail per case plus which rules no case asserts on or ever triggers.

Input Schema

NameRequiredDescriptionDefault
casesYesFixtures: [{ name, document, expect }] where `expect` is a list of rule codes that must fire, a { code: count } map, or [] for a clean lint. Optional `forbid`: codes that must not fire.
contextNoOptional: why you are asking. One sentence — the task you are trying to complete, or what you expect to get back. Never included in the answer and never used to rank; it is read only when a result turns out to be wrong, which is when knowing the intent is what makes the report actionable.
rulesetYesA Spectral ruleset to run instead of the catalog default. Score against rules you never adopted means little — pass your own.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered; the description nonetheless adds real behavioral value by saying the report includes pass/fail per case plus which rules no case asserts on or ever triggers. That reporting behavior is not derivable from the annotations and is the kind of detail an agent needs to interpret results.

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?

A single dense sentence that front-loads the action and appends the reporting behavior; no filler. It is on the long side, but every clause carries information and none is redundant.

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?

With no output schema, the description carries the return-value burden and does so — pass/fail per case plus dead/unasserted rule detection. Combined with full schema coverage and read-only annotations, an agent has enough to call it correctly; only the sibling routing is missing.

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% and the `cases` schema property already explains the name/document/expect/forbid shape, so the description is largely restating it. The mention of the three expectation forms reinforces but does not extend the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Specific verb and resource: 'Run a ruleset against fixture documents with expectations', with the expectation forms spelled out (must-fire codes, exact counts, clean lint). It clearly describes a test-harness operation rather than a linter or validator, but never names the nearby siblings (validate_ruleset, document_ruleset) it differs from, so the distinction is inferred rather than stated.

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 fixture/expectation framing implies the use case — verifying a ruleset behaves as intended — but there is no explicit when-to-use vs validate_ruleset or document_ruleset guidance, and no exclusions. An agent can guess correctly, but must infer the boundary.

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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