Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add AlanHuang168/AI-Project-Workflow --skill discoverygit clone --depth 1 https://github.com/AlanHuang168/AI-Project-WorkflowWrote 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/alanhuang168/ai-project-workflow/discovery)<a href="https://agentmods.dev/skills/alanhuang168/ai-project-workflow/discovery"><img src="https://agentmods.dev/badge/skills/alanhuang168/ai-project-workflow/discovery/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/alanhuang168/ai-project-workflow/discovery"><img src="https://agentmods.dev/badge/skills/alanhuang168/ai-project-workflow/discovery.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 | $0.00013 | $0.00127 |
| Opus 5 | $0.00006 | $0.00063 |
| Sonnet 5 | $0.00003 | $0.00025 |
| Haiku 4.5 | $0.00001 | $0.00013 |
Grade A, and why
discovery 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 9d 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.
What it actually says
Goal
Discover the project requirements, constraints, assumptions, and risks before implementation.
Inputs
- User request
- Existing project context
- Known constraints
Steps
- Identify project goals and non-goals.
- Record constraints, assumptions, and risks.
- Confirm unclear requirements before implementation.
Outputs
docs/DISCOVERY.md
Acceptance Criteria
- Requirements and risks are written down.
- Open questions are visible before implementation starts.
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.
- 9d ago First seen · 32 lines · 13 tokens per session scan A a3795b158a27
discovery is a skill published in the GitHub repository AlanHuang168/AI-Project-Workflow (28 stars, last pushed 1mo ago), licensed MIT. It adds 13 tokens to every session and 127 once invoked, about $0.0001 per session on Opus 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.
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