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-tech-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-tech-spec)<a href="https://agentmods.dev/skills/warpdotdev/common-skills/write-tech-spec"><img src="https://agentmods.dev/badge/skills/warpdotdev/common-skills/write-tech-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-tech-spec"><img src="https://agentmods.dev/badge/skills/warpdotdev/common-skills/write-tech-spec.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- 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 | $0.00046 | $0.01673 |
| Opus 5.5 | $0.00018 | $0.00669 |
| Sonnet 5.5 | $0.00009 | $0.00335 |
| Haiku 4.5 | $0.00005 | $0.00167 |
Grade A, and why
write-tech-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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
write-tech-spec
Write a TECH.md spec for a significant feature in Warp.
Overview
The tech spec should translate product intent into an implementation plan that fits the existing codebase, documents architectural choices, and makes the work easier for agents to execute and reviewers to evaluate.
Write specs to specs/<id>/TECH.md, where <id> is one of:
- a Linear ticket number (e.g.
specs/APP-1234/TECH.md) - a GitHub issue id, prefixed with
gh-(e.g.specs/gh-4567/TECH.md) - a short kebab-case feature name (e.g.
specs/vertical-tabs-hover-sidecar/TECH.md)
Match the id used by the sibling PRODUCT.md when one exists. specs/ should contain only id-named directories as direct children.
Ticket / issue references are optional. If the user has a Linear ticket or GitHub issue, use its id. If they don't, ask them for a feature name to use as the directory. Only create a new Linear ticket or GitHub issue when the user explicitly asks for one; in that case use the Linear MCP tools or gh CLI respectively (and ask_user_question if team, labels, or repo are unclear).
When to use
Use this skill when the implementation spans multiple modules, has meaningful architectural tradeoffs, or when reviewers will benefit from seeing the plan before or alongside the code. For pure UI changes or straightforward fixes, a tech spec is often unnecessary.
Prefer to have a PRODUCT.md first so the technical plan is anchored to agreed behavior. If the implementation is still too uncertain, build an e2e prototype first and then write the tech spec from what was learned.
Research before writing
Before drafting, read the product spec (if any), inspect the relevant code, and identify the main files, types, data flow, and ownership boundaries. Do not guess about current architecture when the code can be inspected directly.
When referencing relevant code chunks in the spec, prefer commit-pinned references so future readers can inspect the exact code you researched. Capture the current commit SHA for each repository you inspected (for example, git rev-parse HEAD) and, when possible, make file references Markdown links to the corresponding GitHub blob/<sha>/...#Lx-Ly URL. Use the linked text to keep the path readable in the spec.
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 · 96 lines · 46 tokens per session scan A ead1a1aaad95
write-tech-spec is a skill published in the GitHub repository warpdotdev/common-skills (636 stars, last pushed today), licensed MIT. It adds 46 tokens to every session and 1,673 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.
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