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 vasilyu1983/AI-Agents-public --skill docs-ai-prdgit clone --depth 1 https://github.com/vasilyu1983/AI-Agents-publicWrote 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/vasilyu1983/ai-agents-public/docs-ai-prd)<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/docs-ai-prd"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/docs-ai-prd/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/vasilyu1983/ai-agents-public/docs-ai-prd"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/docs-ai-prd.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00036 | $0.04294 |
| Opus 5 | $0.00018 | $0.02147 |
| Sonnet 5 | $0.00007 | $0.00859 |
| Haiku 4.5 | $0.00004 | $0.00429 |
Grade A, and why
docs-ai-prd 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 12d 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 — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PRDs, Specs, and Project Context
Use this skill to create decision-first PRDs, tech specs, acceptance criteria, and tool-aware project context for coding assistants.
This skill owns what the implementation agent needs to know and how that context should be structured. It does not own general documentation cleanup or canonical docs maintenance.
Workflow
- Pick the deliverable.
- Gather evidence, constraints, and dependencies.
- Choose the canonical context surface for the target tool or team workflow.
- Write decisions first.
- Add acceptance criteria, rollout gates, and source-backed facts.
- Validate with the relevant checklist before handoff.
ASCII Flow
Request
|
v
Classify deliverable
|-- PRD / brief -------------------> assets/prd/
|-- technical spec ----------------> assets/spec/
|-- story / acceptance criteria ---> assets/stories/
|-- agent handoff context ---------> assets/planning/ + tool context files
|
v
Gather evidence + constraints + dependencies
|
v
Choose context surface
|-- Claude Code -----> CLAUDE.md / scoped Claude files
|-- Codex -----------> AGENTS.md / scoped instructions
|-- Copilot ---------> .github/copilot-instructions.md
|-- Cursor ----------> .cursor/rules/ or AGENTS.md
|
v
Write decisions first
|
v
Add measurable acceptance criteria + rollout / rollback gates
|
v
Validate paths, claims, risks, and handoff readiness
Quick Reference
| Need | Start Here |
|---|---|
| core PRD | assets/prd/prd-template.md |
| AI feature PRD | assets/prd/ai-prd-template.md |
| technical design | assets/spec/tech-spec-template.md |
| story map or backlog framing | assets/stories/story-mapping-template.md |
| acceptance criteria | assets/stories/gherkin-example-template.md |
| planning checklist | assets/planning/planning-checklist.md |
| agentic handoff | assets/planning/agentic-session-template.md |
| minimal agent context files | assets/minimal-claudemd.md, assets/minimal-agents.md |
| cross-tool context layering | assets/cross-tool-context.md |
What ships with it
49 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 315 B
- assets/api-service-context.md 9.6 KB
- assets/architecture-context.md 3.4 KB
- assets/cli-context.md 5.7 KB
- assets/conventions-context.md 2.9 KB
- assets/cross-tool-context.md 5.0 KB
- assets/dependencies-context.md 3.8 KB
- assets/go-context.md 8.9 KB
- assets/key-files-context.md 3.5 KB
- assets/library-context.md 6.0 KB
- assets/metrics/agentic-coding-metrics-template.md 3.6 KB
- assets/minimal-agents.md 1.7 KB
- assets/minimal-claudemd.md 1.8 KB
- assets/nodejs-context.md 7.1 KB
- assets/planning/agentic-session-template.md 4.5 KB
- assets/planning/planning-checklist.md 3.4 KB
- assets/prd/ai-prd-template.md 5.8 KB
- assets/prd/prd-template.md 3.1 KB
- assets/prompting/prompt-playbook.md 4.1 KB
- assets/prompting/structured-prompt-examples.md 3.4 KB
- assets/python-context.md 8.1 KB
- assets/react-context.md 9.6 KB
- assets/spec/tech-spec-template.md 4.7 KB
- assets/stories/gherkin-example-template.md 2.4 KB
- assets/stories/story-mapping-template.md 3.9 KB
- assets/tribal-knowledge-context.md 3.2 KB
- assets/web-app-context.md 5.6 KB
- data/sources.json 18 KB
- learnings.consolidated.md 587 B
- learnings.md 502 B
- references/acceptance-criteria-patterns.md 6.5 KB
- references/agentic-coding-best-practices.md 4.4 KB
- references/architecture-extraction.md 9.0 KB
- references/code-graph-spec-patterns.md 802 B
- references/convention-mining.md 9.6 KB
- references/docs-audit-commands.md 4.6 KB
- references/operational-guide.md 1.9 KB
- references/pm-team-collaboration.md 13 KB
- references/prd-review-facilitation.md 7.2 KB
- references/prompt-engineering-patterns.md 4.7 KB
- references/requirements-checklists.md 4.1 KB
- references/security-review-checklist.md 4.4 KB
- references/spec-driven-dev-landscape.md 2.8 KB
- references/stakeholder-alignment.md 6.8 KB
- references/tool-comparison-matrix.md 3.0 KB
- references/traditional-prd-writing.md 30 KB
- references/tribal-knowledge-recovery.md 9.1 KB
- references/vibe-coding-patterns.md 8.5 KB
- scripts/validate_sources.py 5.8 KB runs code
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.
- 12d ago First seen · 281 lines · 36 tokens per session scan A 83eb70d6859a
docs-ai-prd is a skill published in the GitHub repository vasilyu1983/AI-Agents-public (87 stars, last pushed 10d ago), licensed MIT. It adds 36 tokens to every session and 4,294 once invoked, about $0.0002 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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