Borrowing it
Nothing to install: this file belongs to YougLin-dev/Aha-Loop. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/YougLin-dev/Aha-Loop/main/.agents/skills/vision/SKILL.mdgit clone --depth 1 https://github.com/YougLin-dev/Aha-LoopWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/youglin-dev/aha-loop/vision)<a href="https://agentmods.dev/skills/youglin-dev/aha-loop/vision"><img src="https://agentmods.dev/badge/skills/youglin-dev/aha-loop/vision/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/youglin-dev/aha-loop/vision"><img src="https://agentmods.dev/badge/skills/youglin-dev/aha-loop/vision.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00040 | $0.01795 |
| Opus 5.5 | $0.00016 | $0.00718 |
| Sonnet 5.5 | $0.00008 | $0.00359 |
| Haiku 4.5 | $0.00004 | $0.00179 |
Grade A, and why
vision scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 337 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- Read
project.vision.mdfrom the project root - Validate all required sections are present
- Extract and structure the requirements
- Identify project type and scale
- Output analysis to guide architecture decisions
- Save analysis to
project.vision-analysis.md
Input: project.vision.md
The vision document should contain:
Required Sections
| Section | Purpose |
|---|---|
| What | One-sentence description of the project |
| Why | Motivation and problem being solved |
| Target Users | Who will use this product |
| Success Criteria | Measurable definition of success |
Optional Sections
| Section | Purpose |
|---|---|
| Constraints | Technical, budget, or time limitations |
| Inspirations | Reference products or desired style |
| Non-Goals | What the project explicitly won't do |
Analysis Process
Step 1: Validate Vision Document
Check that project.vision.md exists and contains required sections:
## 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:
| Type | Characteristics |
|---|---|
| CLI Tool | Command-line interface, no UI |
| Web App | Browser-based, frontend + backend |
| API Service | Backend only, REST/GraphQL |
| Library | Reusable code package |
| Desktop App | Native desktop application |
| Mobile App | iOS/Android application |
| Full Stack | Complete web application |
| Infrastructure | DevOps, deployment tools |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 337 lines · 40 tokens per session scan A d8eca0e1d9db
vision is a skill published in the GitHub repository YougLin-dev/Aha-Loop (178 stars, last pushed 9mo ago), licensed MIT. It adds 40 tokens to every session and 1,795 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
vision compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| visionYougLin-dev/Aha-Loop | Skill | 178 | 9mo ago | MIT | A | 40 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |