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 JakubMikolajek/codex-skills-collection --skill product-intentgit clone --depth 1 https://github.com/JakubMikolajek/codex-skills-collectionWrote 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/jakubmikolajek/codex-skills-collection/product-intent)<a href="https://agentmods.dev/skills/jakubmikolajek/codex-skills-collection/product-intent"><img src="https://agentmods.dev/badge/skills/jakubmikolajek/codex-skills-collection/product-intent/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/jakubmikolajek/codex-skills-collection/product-intent"><img src="https://agentmods.dev/badge/skills/jakubmikolajek/codex-skills-collection/product-intent.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 | $0.00076 | $0.01630 |
| Opus 5 | $0.00038 | $0.00815 |
| Sonnet 5 | $0.00015 | $0.00326 |
| Haiku 4.5 | $0.00008 | $0.00163 |
Grade A, and why
product-intent 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Intent
This skill bridges business requirements and technical implementation. It ensures the team is building the right thing before building it well, and verifies the right thing was actually delivered after.
When to Use
- User describes a feature without stating a clear user goal or success condition
- Task involves a new user-facing flow, screen, or interaction
- Implementation plan exists but no one has asked "why does this matter to the user?"
- After implementation to verify the shipped code actually satisfies the stated user need
- When
implementation-gap-analysissignals technical completeness but the feature still feels wrong - Before
task-analysisorarchitecture-designwhen the feature scope is ambiguous - When a stakeholder or ticket describes what to build but not for whom or why
When NOT to Use
- Task is purely infrastructure, refactoring, or developer tooling with no end-user surface
- Product intent is already clearly documented and agreed upon in a PRD or ticket — skip directly to
task-analysis - Task is a bug fix with a clear reproduction — bug fixes restore existing intent, not establish new intent
- User explicitly says "I know what I want, help me build it"
Core Principles
Intent Before Architecture
Do not let technical decisions precede intent clarity. A perfectly architected system that solves the wrong problem is a failure. Run this skill before architecture-design and task-analysis when the user goal is not explicit.
Measurable Success Criteria
Vague acceptance criteria ("user can see their data") are useless for verification. Every success criterion must be concrete enough to pass or fail a manual or automated test.
Bad: "User can manage their documents" Good: "User can upload a document ≤10MB, see it listed within 2 seconds, and delete it — with the deletion reflected immediately in the list"
Anti-Goals Are First-Class
Stating what a feature explicitly does NOT do is as valuable as stating what it does. Anti-goals prevent scope creep, keep the implementation focused, and give agents a basis for declining out-of-scope requests.
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 · 172 lines · 76 tokens per session scan A 5d5c39585750
product-intent is a skill published in the GitHub repository JakubMikolajek/codex-skills-collection (5 stars, last pushed 7d ago), licensed MIT. It adds 76 tokens to every session and 1,630 once invoked, about $0.0004 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…