ambiguity-detector

Detects and analyzes ambiguous language in software requirements and user stories. Use when reviewing requirements documents, user stories, specifications, or any software requirement text to identify vague quantifiers, unclear scope, undefined terms, missing edge cases, subjective language, and incomplete specifications. Provides detailed analysis with clarifying questions and suggested improvements.

1.30x

Quality

81%

Does it follow best practices?

Impact

99%

1.30x

Average score across 3 eval scenarios

Securityby

Passed

No findings from the security scan

Quality

Content

67%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, actionable analysis skill with clear sequencing and good reference navigation. Its main weakness is conciseness: several sections restate the description or duplicate reference content that could be trimmed.

Suggestions

Remove or compress the 'Core Capabilities' section since it restates the frontmatter description without adding new information.

Trim the inline 10-pattern list in Step 2 to a brief pointer to references/ambiguity_patterns.md, keeping only the pattern names rather than full word lists already covered by the reference.

Shorten the closing 'Example Analysis' section to a compact worked example, moving the full annotated walkthrough into a reference file to reduce body length.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient but includes unnecessary padding: the 'Core Capabilities' section restates the description, and the inline 10-pattern list and long worked example analysis could be tightened since comprehensive detail already lives in the reference files.	3 / 5
Actionability	Provides concrete, reusable artifacts (a question-structure template, a severity rubric with examples, and a copy-paste report markdown template), though a few workflow steps like 'Read Requirements Thoroughly' remain generic.	4 / 5
Workflow Clarity	Steps 1–6 are clearly sequenced and supported by Best Practices and Common Pitfalls checklists, but there are no explicit validation/checkpoint steps within the flow (acceptable here since analysis is read-only, so the destructive-cap does not apply).	4 / 5
Progressive Disclosure	References are clearly signaled both inline ('Use references/ambiguity_patterns.md') and in a Resources section, with a compact summary in the body and detail in the reference files; minor organization gaps from the inline report-structure duplication.	4 / 5
	Total	15 / 20 Passed

Description

96%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

An exemplary description that clearly states concrete capabilities and provides an explicit 'Use when...' trigger with natural domain terms. The only minor weakness is a small overlap risk with general requirements-review skills.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions (detect/analyze ambiguous language, identify six named pattern categories, provide analysis with clarifying questions and suggested improvements), giving comprehensive coverage rather than vague abstraction.	5 / 5
Completeness	It explicitly answers both 'what' (detects and analyzes ambiguous language) and 'when' (Use when reviewing requirements documents, user stories, specifications) with concrete trigger phrases.	5 / 5
Trigger Term Quality	The 'Use when reviewing requirements documents, user stories, specifications, or any software requirement text' clause covers the natural phrases a user would say, including synonyms for the domain.	5 / 5
Distinctiveness Conflict Risk	The ambiguity-in-requirements niche is mostly distinct with clear triggers, but there is minor overlap risk with broader requirements-review or document-review skills.	4 / 5
	Total	19 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: ArabelaTso/Skills-4-SE
Path: skills/ambiguity-detector/SKILL.md
Commit: 4f38503

Reviewed: 5 days ago

Table of Contents

Discovery Implementation Validation

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