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

92%

Does it follow best practices?

Impact

99%

1.30x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Quality

Content

85%

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

This is a well-structured, highly actionable skill for requirements ambiguity detection. Its strengths are the concrete pattern catalog, clear severity framework, and complete worked examples. The main weakness is moderate verbosity - the 'Core Capabilities' intro, 'Best Practices', and 'Common Pitfalls' sections add tokens without proportional value since Claude would naturally apply this judgment.

Suggestions

Remove or significantly condense the 'Core Capabilities' section - the detailed workflow already demonstrates these capabilities

Merge 'Best Practices' and 'Common Pitfalls' into a brief 'Judgment Guidelines' section with just the key discriminators (when to flag vs. not flag)

Dimension	Reasoning	Score
Conciseness	The skill is moderately efficient but includes some unnecessary explanation. The 'Core Capabilities' section lists what Claude can do (which is redundant given the detailed workflow), and some sections like 'Best Practices' and 'Common Pitfalls' contain guidance Claude would naturally apply. The content could be tightened by ~30%.	2 / 3
Actionability	Highly actionable with concrete patterns to detect, specific word lists to flag, clear severity classifications with examples, structured question templates, and a complete example analysis showing input-to-output transformation. The report format is copy-paste ready.	3 / 3
Workflow Clarity	Clear 6-step sequential workflow with explicit checkpoints. Each step has defined inputs and outputs. The process flows logically from reading requirements through pattern detection, severity classification, question generation, alternative suggestions, to final report creation.	3 / 3
Progressive Disclosure	Well-structured with clear sections and appropriate references to external files (ambiguity_patterns.md, question_templates.md, report_template.json). The main skill provides a complete overview while pointing to detailed resources for deeper information. Navigation is clear and one-level deep.	3 / 3
	Total	11 / 12 Passed

Description

100%

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

This is an excellent skill description that hits all the key criteria. It provides specific concrete actions, includes natural trigger terms users would actually say, explicitly states both what the skill does and when to use it, and occupies a clear niche that won't conflict with other skills.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: 'identify vague quantifiers, unclear scope, undefined terms, missing edge cases, subjective language, and incomplete specifications' plus 'provides detailed analysis with clarifying questions and suggested improvements.'	3 / 3
Completeness	Clearly answers both what ('Detects and analyzes ambiguous language... identify vague quantifiers, unclear scope...') AND when ('Use when reviewing requirements documents, user stories, specifications, or any software requirement text').	3 / 3
Trigger Term Quality	Excellent coverage of natural terms users would say: 'requirements documents', 'user stories', 'specifications', 'software requirement text', 'ambiguous language', 'vague', 'unclear' - these match how users naturally describe this need.	3 / 3
Distinctiveness Conflict Risk	Clear niche focused specifically on requirements ambiguity analysis - distinct from general code review, documentation, or writing skills. The combination of 'requirements', 'user stories', and 'ambiguous language' creates a unique trigger profile.	3 / 3
	Total	12 / 12 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 — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: ArabelaTso/Skills-4-SE
Commit: 0f00a4f

Reviewed: 4 months ago

Table of Contents

Discovery Implementation Validation

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