Borrowing it
Nothing to install: this file belongs to warpdotdev/common-skills. 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/warpdotdev/common-skills/main/.agents/skills/write-product-spec/SKILL.mdgit clone --depth 1 https://github.com/warpdotdev/common-skillsWrote 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/warpdotdev/common-skills/write-product-spec)<a href="https://agentmods.dev/skills/warpdotdev/common-skills/write-product-spec"><img src="https://agentmods.dev/badge/skills/warpdotdev/common-skills/write-product-spec/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/warpdotdev/common-skills/write-product-spec"><img src="https://agentmods.dev/badge/skills/warpdotdev/common-skills/write-product-spec.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
SkillSpector: 1 finding, up to low
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- low Excessive Agency · line 14 Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
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 | $0.00072 | $0.02792 |
| Opus 5.5 | $0.00029 | $0.01117 |
| Sonnet 5.5 | $0.00014 | $0.00558 |
| Haiku 4.5 | $0.00007 | $0.00279 |
Grade A, and why
write-product-spec 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 1mo 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 — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
write-product-spec
Write a PRODUCT.md spec for a significant feature in Warp.
Overview
The product spec should make the desired behavior unambiguous enough that an agent can implement it correctly and avoid regressions. Describe the feature purely from the user's perspective — what the user sees, does, and experiences, and the invariants that must hold for them. Do not include implementation details (internal types, state layout, module boundaries, data flow, algorithms).
"User" is not limited to the end user of the Warp app. It means whoever consumes the surface being designed:
- For UI / UX features: the human using Warp.
- For a data model: the code that reads and writes that model.
- For an API, protocol, or library: the callers of that API — other services, client code, plugins, or agents.
- For a CLI tool or developer-facing surface: the developer invoking it.
The spec should describe behavior from that consumer's perspective: the shape of the surface, the operations they can perform, what they see back, invariants they can rely on, and edge cases they must handle — without prescribing how the surface is implemented underneath.
Implementation details, validation, and test planning live in a companion TECH.md, produced by the write-tech-spec skill. Writing the product spec is usually the first step of a two-step process: once PRODUCT.md is agreed on, invoke write-tech-spec to produce TECH.md for the same feature (or let the user know that's the expected next step). The product spec should be written so the tech spec can be written directly from it.
Write specs to specs/<id>/PRODUCT.md, where <id> is one of:
- a Linear ticket number (e.g.
specs/APP-1234/PRODUCT.md) - a GitHub issue id, prefixed with
gh-(e.g.specs/gh-4567/PRODUCT.md) - a short kebab-case feature name (e.g.
specs/vertical-tabs-hover-sidecar/PRODUCT.md)
specs/ should contain only id-named directories as direct children — no engineer-named subdirectories.
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.
- 1mo ago First seen · 165 lines · 72 tokens per session scan A c517e5d21063
write-product-spec is a skill published in the GitHub repository warpdotdev/common-skills (636 stars, last pushed today), licensed MIT. It adds 72 tokens to every session and 2,792 once invoked, about $0.0003 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.
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