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.

Install with Tessl CLI

npx tessl i github:ArabelaTso/Skills-4-SE --skill ambiguity-detector

What are skills?

Review — 92%

Does it follow best practices?

Validation — 11 / 11 Passed

Validation for skill structure

SKILL.md

Review

Evals

Evaluation results

98%

10%

Checkout Flow Requirements Analysis

Structured ambiguity report with severity classification

Criteria

Without context

With context

AMB-XXX numbering

100%

Summary section with counts

100%

Recommendations section

100%

Requirement ID reference

100%

Impact explanation

100%

Severity-ordered presentation

100%

Vague quantifier detected

100%

Subjective language detected

100%

Weak conditional detected

100%

Clarifying questions with options

100%

Suggested clarification per ambiguity

75%

100%

Avoids flagging non-issues

50%

Missing edge cases pattern

100%

Without context: $0.3094 · 3m 32s · 8 turns · 13 in / 8,043 out tokens

With context: $0.8023 · 6m 4s · 26 turns · 32 in / 13,930 out tokens

100%

38%

API Requirements Analysis for CI/CD Integration

JSON output format with report_template structure

Criteria

Without context

With context

JSON output file

100%

ambiguity_report root key

100%

metadata section

62%

100%

ambiguity id field

100%

ambiguity_type field

100%

impact field

62%

100%

examples field

100%

summary_by_type

25%

100%

summary_by_severity

75%

100%

recommendations array

100%

alternatives.md file

100%

2-3 alternatives per ambiguity

100%

Temporal ambiguity typed

100%

Without context: $0.4636 · 4m 24s · 14 turns · 21 in / 10,886 out tokens

With context: $1.0441 · 6m 31s · 25 turns · 29 in / 16,966 out tokens

100%

21%

Requirements Annotation for Inventory Management System

Inline annotations and selective flagging

Criteria

Without context

With context

Inline annotation file

100%

Annotations visually distinct

100%

Annotation includes clarifying question

50%

100%

Summary table file

100%

Summary table columns

62%

100%

Does NOT flag defined glossary terms

100%

Vague temporal flagged

100%

Vague quantifier flagged

100%

Unclear scope or reference flagged

100%

Annotation explains why it matters

50%

100%

Severity assigned

100%

Without context: $0.2591 · 2m 27s · 10 turns · 15 in / 5,291 out tokens

With context: $0.9044 · 6m 29s · 25 turns · 3,911 in / 13,876 out tokens

Evaluated: about 11 hours ago
Agent: Claude Code

Table of Contents

Checkout Flow Requirements Analysis API Requirements Analysis for CI/CD Integration Requirements Annotation for Inventory Management System

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