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QuassLabs API

acceptance_criteria_validator

QA advisor: validate acceptance criteria quality. POST a list of AC (or a story) and get per-AC problems (vague/untestable, non-atomic, no observable outcome) + a missing-coverage flag if there is no failure-path AC, plus a 0-100 score and pass/needs_work verdict. Tells you exactly what to fix. Deterministic, no LLM.

Input Schema

NameRequiredDescriptionDefault
storyNo
strictnessNo
acceptance_criteriaNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses the analysis is deterministic with no LLM, and enumerates exactly what the response contains (per-AC problems, missing failure-path coverage flag, score, verdict). It omits side-effect/auth/rate-limit disclosure and whether both inputs can be combined.

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?

Front-loaded with the role and action, then outputs, then the determinism claim. Dense but every clause carries information; only the 'QA advisor:' framing and 'Tells you exactly what to fix' are slightly promotional.

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?

There is no output schema, and the description does a good job describing the return shape. However, for a 3-parameter tool it never explains strictness behavior, whether story and acceptance_criteria are mutually exclusive, or what happens if neither is supplied (required list is empty).

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 0%, so the description must compensate. It maps 'a list of AC' to acceptance_criteria and 'or a story' to story, but the strictness enum (normal/strict) is never mentioned anywhere, leaving a third of the parameters undocumented.

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?

States a specific verb and resource: 'validate acceptance criteria quality', with concrete outputs (per-AC problems, coverage flag, 0-100 score, verdict). It does not differentiate itself from close siblings like story_lint, ticket_lint, or coverage_check, so an agent must infer the boundary.

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?

'POST a list of AC (or a story)' implies the two input modes, but there is no explicit statement of when to pick this over coverage_check or story_lint, nor any exclusion or prerequisite. Usage is inferable rather than stated.

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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