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 liqiongyu/lenny_skills_plus --skill writing-prdsgit clone --depth 1 https://github.com/liqiongyu/lenny_skills_plusWrote 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/liqiongyu/lenny_skills_plus/writing-prds)<a href="https://agentmods.dev/skills/liqiongyu/lenny_skills_plus/writing-prds"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/writing-prds/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/liqiongyu/lenny_skills_plus/writing-prds"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/writing-prds.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 | $0.00028 | $0.01905 |
| Opus 5 | $0.00014 | $0.00953 |
| Sonnet 5 | $0.00006 | $0.00381 |
| Haiku 4.5 | $0.00003 | $0.00191 |
Grade A, and why
writing-prds 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.
How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing PRDs
Scope
Covers
- Turning a product idea into a decision-ready PRD with unambiguous scope, requirements, and success metrics
- Optionally producing a PR/FAQ (press release + FAQ) to force customer-centric narrative first
- For AI features: adding a Prompt Set + Eval Spec so “requirements” are testable and continuously checkable
When to use
- “Write a PRD / product spec / requirements doc for this feature.”
- “Turn these messy notes into a PRD we can align on.”
- “Create a PR/FAQ and then a PRD.”
- “This is an AI feature; I need evals + prompts to define behavior.”
When NOT to use
- You’re still choosing what strategy/market to pursue (do product vision / strategy first)
- You need discovery from scratch (research plan, problem validation) more than requirements -> use
problem-definition - You need a detailed engineering design doc (APIs, schemas, low-level architecture)
- You’re prioritizing among many initiatives -> use
working-backwardsor roadmap prioritization first - You need build-ready interaction specs, user flows, or prototype briefs -> use
writing-specs-designs - You need to define or refresh the success metric / North Star before writing requirements -> use
writing-north-star-metrics
Inputs
Minimum required
- Product + target user/customer segment
- Problem statement + why now (what changed, what’s broken, or what opportunity exists)
- Goal(s) + non-goal(s) + key constraints (timeline, policy/legal, platform, dependencies)
- Success metric(s) + 2–5 guardrails (quality, safety, cost, latency, trust)
If it’s an AI feature (additionally)
- What the model/system should do vs must never do (policy + safety)
- Concrete examples of desired and undesired outputs
- How correctness will be evaluated (offline tests, human review, online metrics)
Missing-info strategy
- Ask up to 5 questions from references/INTAKE.md.
- If answers are still missing, proceed with clearly labeled assumptions and provide 2–3 options (scope, metric, rollout).
What ships with it
13 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.
- eval/eval_config.json 445 B
- eval/SHOWCASE.md 5.3 KB
- eval/with_skill.md 35 KB
- eval/without_skill.md 23 KB
- README.md 1.5 KB
- references/CHECKLISTS.md 1.4 KB
- references/EXAMPLES.md 1.3 KB
- references/INTAKE.md 2.4 KB
- references/RUBRIC.md 2.8 KB
- references/SOURCE_SUMMARY.md 2.0 KB
- references/TEMPLATES.md 5.0 KB
- references/WORKFLOW.md 2.8 KB
- skillpack.json 360 B
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 · 138 lines · 28 tokens per session scan A 748040d8322f
writing-prds is a skill published in the GitHub repository liqiongyu/lenny_skills_plus (52 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 28 tokens to every session and 1,905 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 2026-09-03.
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