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quality_checklist

Retrieve artifact-specific quality checklists for user stories, test plans, test cases, API contracts, and bug reports. Apply actionable criteria to verify completeness and correctness.

Instructions

Retorna checklist de qualidade para um artefato específico: user story, plano de testes, caso de teste, código de teste, contrato de API, suíte completa, bug report ou critérios de aceitação.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
artifact_typeYesTipo do artefato.
artifact_contentNoConteúdo do artefato para análise específica (opcional).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv2.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description must fully disclose behavioral traits. It only states it returns a checklist, but does not explain whether the optional artifact_content is used for analysis or ignored, whether the checklist is generic or content-specific, or any side effects. Safety and permissions are entirely undisclosed.

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?

A single sentence that front-loads the primary action (returns checklist) and lists supported artifact types. Every word is essential; no filler or repetition.

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

Completeness2/5

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

Given no output schema and no annotations, the description should cover return format, whether artifact_content is necessary, and typical usage context. It does not. For a 2-parameter tool with an enum, the description is too minimal to enable confident invocation by an AI agent.

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% (both parameters have descriptions). The description adds natural language expansion of the artifact_type enum values, but does not add any new meaning beyond what the schema already provides. Baseline is 3, and the description barely meets it.

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?

The description clearly states the tool returns a quality checklist for a specific artifact type and lists eight concrete types (user story, test plan, etc.). This provides a specific verb+resource combination and helps distinguish from some siblings, though it does not explicitly differentiate from 'security_test_checklist'.

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

Usage Guidelines2/5

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

No guidance is given on when to use this tool versus alternatives like 'analyze_user_story' or 'security_test_checklist'. There is no mention of prerequisites, when not to use it, or how to choose artifact types. The agent must infer usage from the tool name and sibling list.

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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