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Agent skill

Vision

by YougLin-dev in YougLin-dev/Aha-Loop

Parses and analyzes project vision to extract structured requirements.

MITAuto-check passed

Install Vision

skills CLI
$ npx skills add YougLin-dev/Aha-Loop --skill vision -a claude-code

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

GitHub CLI
$ gh skill install YougLin-dev/Aha-Loop vision --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/YougLin-dev/Aha-Loop.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/vision .claude/skills/vision && 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
vision
GitHub stars
181
Token cost
~2k tokens
SKILL.md length
486 words
Files
1
Skills in repo
15
Repo updated
First seen
Licence
MIT

At a glance

Parses and analyzes project vision to extract structured requirements.

  • Works in 5 steps: Validate Vision Document → Identify Project Type → Estimate Project Scale → …
  • : analyze vision
  • SKILL.md covers Workspace Mode Note, The Job, Input: project.vision.md and Analysis Process, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Vision is an agent skill from YougLin-dev/Aha-Loop. Parses and analyzes project vision to extract structured requirements. Use at project start to understand goals, scope, and constraints. Triggers on: analyze vision, parse project goals, understand requirements.

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: [MVP] Aha Loop is a fully autonomous AI development system, extended from the core ideas of Ralph. It's not just an execution engine, but a complete AI development framework with… The licence is MIT.

When your agent uses it

  • : analyze vision
  • Parse project goals
  • Understand requirements

Example prompts

  • “Use the vision skill to parse and analyzes project vision to extract structured requirements”
  • “/vision”

Workflow steps

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

  1. Validate Vision Document
  2. Identify Project Type
  3. Estimate Project Scale
  4. Extract Core Features
  5. Identify Technical Implications

What it can do on your machine

Read from SKILL.md and the folder at commit 8d799b2. 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

Vision loads about 2k tokens when it runs. Until then it costs about 55 tokens; SKILL.md has 486 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~55
When it runs · the whole SKILL.md, loaded when a task matches
~2k

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 YougLin-dev/Aha-Loop at commit 8d799b2, republished under its MIT licence (© YougLin-dev). 486 words, ~1,985 tokens.

Download SKILL.mdSave it as .claude/skills/vision/SKILL.md (or your agent's skills folder).
name
vision
description
Parses and analyzes project vision to extract structured requirements. Use at project start to understand goals, scope, and constraints. Triggers on: analyze vision, parse project goals, understand requirements.

Vision Analysis Skill

Parse the project vision document and extract structured requirements for architecture and planning.

Workspace Mode Note

When running in workspace mode, all paths are relative to .aha-loop/ directory:

  • Vision file: .aha-loop/project.vision.md
  • Analysis output: .aha-loop/project.vision-analysis.md

The orchestrator will provide the actual paths in the prompt context.

The Job

  1. Read project.vision.md from the project root
  2. Validate all required sections are present
  3. Extract and structure the requirements
  4. Identify project type and scale
  5. Output analysis to guide architecture decisions
  6. Save analysis to project.vision-analysis.md

Input: project.vision.md

The vision document should contain:

Required Sections
SectionPurpose
WhatOne-sentence description of the project
WhyMotivation and problem being solved
Target UsersWho will use this product
Success CriteriaMeasurable definition of success
Optional Sections
SectionPurpose
ConstraintsTechnical, budget, or time limitations
InspirationsReference products or desired style
Non-GoalsWhat the project explicitly won't do

Analysis Process

Step 1: Validate Vision Document

Check that project.vision.md exists and contains required sections:

markdown
## Validation Checklist
- [ ] What section present and clear
- [ ] Why section explains motivation
- [ ] Target Users defined
- [ ] Success Criteria are measurable

If sections are missing or unclear, document what's needed before proceeding.

Step 2: Identify Project Type

Classify the project:

TypeCharacteristics
CLI ToolCommand-line interface, no UI
Web AppBrowser-based, frontend + backend
API ServiceBackend only, REST/GraphQL
LibraryReusable code package
Desktop AppNative desktop application
Mobile AppiOS/Android application
Full StackComplete web application
InfrastructureDevOps, deployment tools
Step 3: Estimate Project Scale
ScaleStoriesDurationComplexity
Small5-15DaysSingle component
Medium15-50WeeksMultiple components
Large50-200MonthsFull system
Enterprise200+QuartersMultiple systems
Step 4: Extract Core Features

From the vision, identify:

  1. Must-Have Features - Critical for MVP
  2. Should-Have Features - Important but not blocking
  3. Nice-to-Have Features - Enhancements for later
  4. Out of Scope - Explicitly excluded
Show full SKILL.md (202 more words)Show less
Step 5: Identify Technical Implications

Based on features, note:

  • Data storage needs (database type, scale)
  • Authentication requirements
  • External integrations
  • Performance requirements
  • Security considerations
  • Deployment environment

Output: project.vision-analysis.md

markdown
# Vision Analysis

**Generated:** [timestamp]
**Vision Version:** [hash or date of vision.md]

## Project Classification

- **Type:** [Web App | API Service | CLI Tool | ...]
- **Scale:** [Small | Medium | Large | Enterprise]
- **Estimated Stories:** [range]

## Core Requirements

### Must-Have (MVP)
1. [Feature 1]
2. [Feature 2]
3. ...

### Should-Have (Post-MVP)
1. [Feature 1]
2. ...

### Nice-to-Have (Future)
1. [Feature 1]
2. ...

### Out of Scope
- [Excluded item 1]
- [Excluded item 2]

## Technical Implications

### Data & Storage
- [Storage needs analysis]

### Authentication & Security
- [Auth requirements]

### Integrations
- [External system integrations]

### Performance
- [Performance requirements]

### Deployment
- [Deployment environment needs]

## Constraints Summary

| Constraint | Impact |
|------------|--------|
| [Constraint 1] | [How it affects decisions] |

## Open Questions

- [ ] [Question that needs clarification]
- [ ] [Another question]

## Recommended Next Steps

1. Run Architect Skill to determine technology stack
2. Address any open questions before proceeding
3. ...

## Architecture Hints

Based on this vision, consider:
- [Hint about architecture approach]
- [Hint about technology category]

Decision Points

When Vision is Unclear

If the vision document lacks detail:

  1. Do NOT guess - Document what's missing
  2. List specific questions - What exactly needs clarification
  3. Provide options - Suggest possible interpretations
  4. Proceed cautiously - Make conservative assumptions and note them
When Scope is Too Large

If estimated scale is "Large" or "Enterprise":

  1. Recommend phased approach - Break into multiple major milestones
  2. Identify MVP subset - What's the smallest useful version
  3. Flag risk - Note that large projects need careful management
When Constraints Conflict

If constraints seem to conflict with goals:

  1. Document the conflict - Be explicit about the tension
  2. Propose resolutions - Suggest possible compromises
  3. Prioritize - Recommend which constraint to relax

Integration with Orchestrator

After vision analysis:

  1. Save project.vision-analysis.md to project root
  2. Signal completion to orchestrator
  3. Architect Skill uses this analysis as input

Example Analysis

Input Vision:

markdown
# Project Vision

## What
A personal finance tracker that helps users manage their budget and track expenses.

## Why
Existing apps are too complex. Users need a simple, focused tool.

## Target Users
Individuals who want basic expense tracking without complexity.

## Success Criteria
- Users can add expenses in under 5 seconds
- Monthly reports generated automatically
- Works offline

## Constraints
- Must be a web app (PWA for offline)
- No paid APIs (keep it free)
- Single developer, limited time

Output Analysis:

markdown
# Vision Analysis

## Project Classification
- **Type:** Web App (PWA)
- **Scale:** Medium
- **Estimated Stories:** 20-35

## Core Requirements

### Must-Have (MVP)
1. Quick expense entry (< 5 seconds)
2. Expense categorization
3. Monthly report generation
4. Offline support (PWA)
5. Data persistence

### Should-Have (Post-MVP)
1. Budget setting and tracking
2. Expense trends visualization
3. Export functionality

### Nice-to-Have (Future)
1. Multiple currencies
2. Receipt photo capture
3. Bank import

### Out of Scope
- Multi-user/sharing features
- Investment tracking
- Tax preparation

## Technical Implications

### Data & Storage
- Local-first (IndexedDB for offline)
- Optional cloud sync later

### Authentication & Security
- Initially: None (local only)
- Later: Simple auth for sync

### Performance
- Critical: Fast expense entry
- PWA service worker for offline

### Deployment
- Static hosting (Netlify, Vercel)
- No backend initially

## Constraints Summary

| Constraint | Impact |
|------------|--------|
| PWA required | Must use service workers, IndexedDB |
| No paid APIs | Use free/open solutions only |
| Limited time | Focus on MVP, defer nice-to-haves |

## Recommended Next Steps

1. Run Architect Skill to select frontend framework
2. Design offline-first data architecture
3. Plan PWA implementation strategy

Checklist

Before completing vision analysis:

  • All required vision sections validated
  • Project type identified
  • Scale estimated
  • Features categorized (must/should/nice/out)
  • Technical implications documented
  • Constraints analyzed
  • Open questions listed
  • Analysis saved to project.vision-analysis.md

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

Files

Just SKILL.md in .agents/skills/vision of YougLin-dev/Aha-Loop.

Open the folder on GitHubat commit 8d799b2

Compare with similar skills

Vision 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.

Vision compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Vision this skillYougLin-dev/Aha-Loop181—~2kAutomated safety check: PassMIT
Fal Visionnexu-io/open-design100k—~295Automated safety check: PassApache-2.0
Extractalirezarezvani/claude-skills28k—~1.4kAutomated safety check: PassMIT
Vision Sftwshobson/agents40k—~2kAutomated safety check: PassMIT
Visiongridaco/grida2.7k—~1.5kAutomated safety check: PassApache-2.0
Requirementsrizsotto/Bear6.5k—~2kAutomated safety check: PassGPL-3.0

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Questions about Vision

What does Vision do?

Parses and analyzes project vision to extract structured requirements. Vision is an agent skill from YougLin-dev/Aha-Loop. Parses and analyzes project vision to extract structured requirements.

When should I use Vision?

Vision fits situations like: : analyze vision; parse project goals; understand requirements.

How do I install Vision in Claude Code?

Run `npx skills add YougLin-dev/Aha-Loop --skill vision -a claude-code`. Or copy the skill folder (.agents/skills/vision in YougLin-dev/Aha-Loop) into .claude/skills/vision in your project. Claude Code loads it when a task matches its description.

How do I install Vision in Codex?

Run `npx skills add YougLin-dev/Aha-Loop --skill vision -a codex`. Or copy the skill folder (.agents/skills/vision in YougLin-dev/Aha-Loop) into .agents/skills/vision in your project. Codex loads it when a task matches its description.

Can I use Vision 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 YougLin-dev/Aha-Loop --skill vision -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/vision, .gemini/skills/vision, .github/skills/vision and .opencode/skills/vision in your project.

What does Vision need to run?

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

Does Vision 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 Vision 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 Vision use?

Vision is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Vision use?

About 2k tokens (SKILL.md is roughly 7.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Vision?

Skills that share tags, products or a category with Vision: Fal Vision (nexu-io/open-design, 100k stars), Extract (alirezarezvani/claude-skills, 28k stars), Vision Sft (wshobson/agents, 40k stars) and Vision (gridaco/grida, 2.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Vision?

YougLin-dev (a GitHub user) maintains it in YougLin-dev/Aha-Loop, which has 181 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on February 3, 2026.

Source: YougLin-dev/Aha-Loop on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.