Agent skill

Requirement Enhancer

by ArabelaTso in ArabelaTso/Skills-4-SE

Iteratively enhance user requirements into clear, complete, actionable specifications through analysis and clarification.

Apache-2.0Auto-check passedProduct & Project Management

Install Requirement Enhancer

skills CLI
$ npx skills add ArabelaTso/Skills-4-SE --skill requirement-enhancer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ArabelaTso/Skills-4-SE requirement-enhancer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ArabelaTso/Skills-4-SE.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/requirement-enhancer .claude/skills/requirement-enhancer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
requirement-enhancer
GitHub stars
253
Token cost
~2.2k tokens
SKILL.md length
775 words
Files
3 (incl. references)
Skills in repo
170
Repo updated
First seen
Licence
Apache-2.0

At a glance

Iteratively enhance user requirements into clear, complete, actionable specifications through analysis and clarification.

  • Works in 6 steps: Initial Analysis → Identify Issues → Formulate Questions → …
  • Users provide initial requirements that need refinement
  • SKILL.md covers Core Principles, Enhancement Workflow, Analysis Framework and Common Ambiguity Patterns, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Requirement Enhancer is an agent skill from ArabelaTso/Skills-4-SE. Iteratively enhance user requirements into clear, complete, actionable specifications through analysis and clarification. Use when: (1) Users provide initial requirements that need refinement, (2) Requirements are vague, incomplete, or ambiguous, (3) Creating formal specifications from informal descriptions, (4) Identifying missing constraints, edge cases, or acceptance criteria, (5) Clarifying assumptions and implicit dependencies, or (6) Preparing requirements for design, implementation, or verification…

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/analysis_framework.md` and `references/examples.md`).

It sits in Product & Project Management, covering User stories and Requirements gathering. The repository describes itself as: A curated list of 180+ useful Claude Skills for Software Engineering and resources for customizing AI for SE workflows. The licence is Apache-2.0.

When your agent uses it

  • Users provide initial requirements that need refinement
  • Requirements are vague
  • Creating formal specifications from informal descriptions
  • Identifying missing constraints

Example prompts

  • “/requirement-enhancer”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Initial Analysis
  2. Identify Issues
  3. Formulate Questions
  4. Incorporate Responses
  5. Enrich with Domain Knowledge
  6. Structure Output

What it can do on your machine

Read from SKILL.md and the folder at commit 4f38503. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Requirement Enhancer loads about 2.2k tokens when it runs, and up to ~7.5k if it reads all its reference files. Until then it costs about 155 tokens; SKILL.md has 775 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~155
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ArabelaTso/Skills-4-SE at commit 4f38503, republished under its Apache-2.0 licence (© ArabelaTso). 775 words, ~2,197 tokens.

Download SKILL.mdSave it as .claude/skills/requirement-enhancer/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
requirement-enhancer
description
Iteratively enhance user requirements into clear, complete, actionable specifications through analysis and clarification. Use when: (1) Users provide initial requirements that need refinement, (2) Requirements are vague, incomplete, or ambiguous, (3) Creating formal specifications from informal descriptions, (4) Identifying missing constraints, edge cases, or acceptance criteria, (5) Clarifying assumptions and implicit dependencies, or (6) Preparing requirements for design, implementation, or verification. Operates interactively: analyze → ask clarifying questions → refine based on responses.

Requirement Enhancer

Transform initial requirements into clear, complete, actionable specifications through iterative analysis and refinement.

Core Principles

Preserve Intent
  • Maintain the user's original goals and vision
  • Do not change fundamental requirements without confirmation
  • Clarify rather than assume
Iterative Refinement
  • Analyze → Ask → Refine → Repeat
  • Ask targeted questions to fill gaps
  • Incorporate user responses progressively
Explicit Over Implicit
  • Make assumptions visible with [ASSUMED] or [INFERRED] labels
  • Distinguish confirmed facts from educated guesses
  • Highlight areas needing clarification
Avoid Over-Specification
  • Do not add unnecessary details without user input
  • Focus on essential requirements first
  • Mark nice-to-have vs. must-have clearly

Enhancement Workflow

1. Initial Analysis

Analyze the requirement across multiple dimensions:

Clarity: Identify vague terms, ambiguous language, undefined metrics Completeness: Find missing functional/non-functional requirements, edge cases Consistency: Detect conflicts, contradictions, terminology issues Feasibility: Note technical concerns, resource constraints Testability: Check for measurable acceptance criteria

2. Identify Issues

Categorize issues by severity:

🔴 Critical: Core functionality undefined, conflicting requirements 🟡 Important: Missing constraints, unclear scope, vague metrics 🟢 Minor: Terminology inconsistencies, formatting issues

3. Formulate Questions

Ask targeted clarification questions:

For ambiguity: "What exactly does [vague term] mean in measurable terms?" For incompleteness: "What should happen when [edge case]?" For conflicts: "How do requirements X and Y work together?" For missing details: "What are the [performance/security/usability] requirements?"

Use the AskUserQuestion tool to present questions clearly.

4. Incorporate Responses

Based on user answers:

  • Update requirements with confirmed information
  • Add [CONFIRMED] labels to user-provided details
  • Keep [ASSUMED] labels for inferences
  • Note [INFERRED] for logical deductions
5. Enrich with Domain Knowledge

Add standard practices when applicable:

For authentication: Password requirements, session management, rate limiting For APIs: Error codes, versioning, rate limits, documentation For data processing: Validation, error handling, performance bounds For web apps: Browser compatibility, accessibility, security (OWASP)

Label enrichments as [STANDARD PRACTICE] or [BEST PRACTICE].

6. Structure Output

Organize enhanced requirement in clear sections:

markdown
## [Requirement Name]

### Overview
[Brief description preserving original intent]

### Functional Requirements
[Detailed functional requirements with IDs]

### Non-Functional Requirements
[Performance, security, usability, etc.]

### Acceptance Criteria
[Testable criteria in Given/When/Then format]

### Assumptions
[Explicit list of assumptions with labels]

### Edge Cases
[Identified edge cases and expected behavior]

### Constraints
[Technical, business, regulatory constraints]

### Out of Scope
[Explicitly excluded items]

Analysis Framework

For detailed analysis dimensions and patterns, see analysis_framework.md.

Key areas to analyze:

  • Clarity and precision
  • Completeness
  • Consistency
  • Feasibility
  • Testability

Common Ambiguity Patterns

Quantifier Ambiguity

Vague: "The system should be fast" Enhanced: "The system MUST respond within 200ms for 95% of requests"

Modal Ambiguity

Vague: "The system should support users" Enhanced: "The system MUST support at least 10,000 concurrent users"

Scope Ambiguity

Vague: "Users can edit documents" Enhanced: "Authenticated users with 'Editor' role can modify content of documents they own"

Temporal Ambiguity

Vague: "Backup data regularly" Enhanced: "Perform incremental backups every 6 hours, full backups daily at 2 AM UTC"

Conditional Ambiguity

Vague: "If user is inactive, log them out" Enhanced: "After 30 min inactivity, warn user. After 35 min total, save work and log out"

Requirement Categories

Functional Requirements (FR)

What the system must do:

  • User actions and system responses
  • Data processing and transformations
  • Business logic and rules
  • Integration points
Show full SKILL.md (321 more words)Show less
Non-Functional Requirements (NFR)

How the system must perform:

  • Performance: Response time, throughput, latency
  • Security: Authentication, authorization, encryption
  • Usability: User experience, accessibility
  • Reliability: Uptime, error rates, recovery
  • Scalability: Load handling, growth capacity
  • Maintainability: Code quality, documentation
Acceptance Criteria (AC)

Testable conditions for requirement satisfaction:

  • Given [precondition]
  • When [action]
  • Then [expected result]

Labeling Conventions

Confirmation Status
  • [CONFIRMED]: User explicitly confirmed
  • [ASSUMED]: Reasonable assumption, needs confirmation
  • [INFERRED]: Logical deduction from confirmed facts
  • [STANDARD PRACTICE]: Industry-standard approach
  • [BEST PRACTICE]: Recommended approach
Priority Levels (RFC 2119)
  • MUST: Mandatory, non-negotiable
  • SHOULD: Highly desired, may be deferred
  • MAY: Optional, nice-to-have
  • MUST NOT: Explicitly forbidden
Risk Indicators
  • 🔴 Critical issue requiring immediate attention
  • 🟡 Important issue to address
  • 🟢 Minor issue or improvement

Output Format

Structure enhanced requirements as Markdown:

markdown
# [Feature/System Name]

## Overview
[Brief description, 2-3 sentences]

## Functional Requirements

### FR-[ID]-001: [Requirement Name]
- **Priority**: MUST/SHOULD/MAY
- **Description**: [Detailed description]
- **Acceptance Criteria**:
  - Given [precondition]
  - When [action]
  - Then [expected result]

## Non-Functional Requirements

### NFR-[ID]-001: [Category]
- **Priority**: MUST/SHOULD/MAY
- **Description**: [Specific requirement with metrics]
- **Measurement**: [How to verify]

## Assumptions
- [CONFIRMED] [User-confirmed assumption]
- [ASSUMED] [Reasonable assumption needing confirmation]
- [INFERRED] [Logical deduction]

## Edge Cases
- **[Scenario]**: [Expected behavior]

## Constraints
- [Technical/business/regulatory constraints]

## Out of Scope
- [Explicitly excluded features or functionality]

Interactive Loop

Round 1: Initial Analysis
  1. Receive initial requirement
  2. Analyze for issues
  3. Ask 3-5 most critical clarification questions
  4. Wait for user responses
Round 2: Refinement
  1. Incorporate user responses
  2. Generate enhanced requirement draft
  3. Identify remaining ambiguities
  4. Ask follow-up questions if needed
  5. Wait for user responses
Round 3: Finalization
  1. Incorporate final responses
  2. Add domain-specific best practices
  3. Complete all sections
  4. Present final enhanced requirement
  5. Confirm with user

Quality Checks

Before finalizing, verify:

✓ All critical ambiguities resolved ✓ Functional and non-functional requirements specified ✓ Acceptance criteria are testable ✓ Assumptions explicitly labeled ✓ Edge cases identified ✓ Constraints documented ✓ Priority levels assigned ✓ Original intent preserved

Examples

For complete before/after examples including:

  • User authentication enhancement
  • Data export feature enhancement
  • Search functionality enhancement

See examples.md.

Tips

  • Start broad: Ask high-level questions first, then drill down
  • Be specific: Ask for concrete examples and metrics
  • Avoid leading questions: Don't suggest answers
  • One topic at a time: Don't overwhelm with too many questions
  • Confirm understanding: Paraphrase user responses to verify
  • Preserve intent: Always check if enhancements align with user goals
  • Label everything: Make confirmation status explicit
  • Iterate: Multiple rounds are normal and expected
  • Know when to stop: Don't over-specify without user input

© ArabelaTso, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/requirement-enhancer of ArabelaTso/Skills-4-SE.

  • SKILL.md
  • references/analysis_framework.md
  • references/examples.md

Open the folder on GitHubat commit 4f38503

Compare with similar skills

Requirement Enhancer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Requirement Enhancer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Requirement Enhancer this skillArabelaTso/Skills-4-SE253—~2.2kAutomated safety check: PassApache-2.0
User Story Writerdeanpeters/Product-Manager-Skills7.2k2 repos~2.9kAutomated safety check: PassCustom licence
PRD Developmentdeanpeters/Product-Manager-Skills7.2k3 repos~6.2kAutomated safety check: PassCustom licence
Feature ForgeJeffallan/claude-skills12k—~1.1kAutomated safety check: PassMIT
Specificationcitypaul/.dotfiles740—~2.2kAutomated safety check: PassCustom licence
Find Gapscitypaul/.dotfiles740—~6.6kAutomated safety check: PassCustom licence

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Questions about Requirement Enhancer

What does Requirement Enhancer do?

Iteratively enhance user requirements into clear, complete, actionable specifications through analysis and clarification. Requirement Enhancer is an agent skill from ArabelaTso/Skills-4-SE. Iteratively enhance user requirements into clear, complete, actionable specifications through analysis and clarification.

When should I use Requirement Enhancer?

Requirement Enhancer fits situations like: users provide initial requirements that need refinement; requirements are vague; creating formal specifications from informal descriptions; identifying missing constraints.

How do I install Requirement Enhancer in Claude Code?

Run `npx skills add ArabelaTso/Skills-4-SE --skill requirement-enhancer -a claude-code`. Or copy the skill folder (skills/requirement-enhancer in ArabelaTso/Skills-4-SE) into .claude/skills/requirement-enhancer in your project. Claude Code loads it when a task matches its description.

How do I install Requirement Enhancer in Codex?

Run `npx skills add ArabelaTso/Skills-4-SE --skill requirement-enhancer -a codex`. Or copy the skill folder (skills/requirement-enhancer in ArabelaTso/Skills-4-SE) into .agents/skills/requirement-enhancer in your project. Codex loads it when a task matches its description.

Can I use Requirement Enhancer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ArabelaTso/Skills-4-SE --skill requirement-enhancer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/requirement-enhancer, .gemini/skills/requirement-enhancer, .github/skills/requirement-enhancer and .opencode/skills/requirement-enhancer in your project.

What does Requirement Enhancer need to run?

SKILL.md names no scripts, command-line tools or credentials: Requirement Enhancer is instructions for the agent only.

Does Requirement Enhancer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Requirement Enhancer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Requirement Enhancer use?

Requirement Enhancer is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Requirement Enhancer use?

About 2.2k tokens (SKILL.md is roughly 8.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.3k tokens, read only when the agent opens those files.

What are the alternatives to Requirement Enhancer?

Skills that share tags, products or a category with Requirement Enhancer: User Story Writer (deanpeters/Product-Manager-Skills, 7.2k stars), PRD Development (deanpeters/Product-Manager-Skills, 7.2k stars), Feature Forge (Jeffallan/claude-skills, 12k stars) and Specification (citypaul/.dotfiles, 740 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Requirement Enhancer?

ArabelaTso (a GitHub user) maintains it in ArabelaTso/Skills-4-SE, which has 253 GitHub stars. The repository holds 170 skills in this directory. The repository was last updated on August 21, 2026.

Source: ArabelaTso/Skills-4-SE on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.