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 jimtin/production-ai --skill client-requirements-to-plangit clone --depth 1 https://github.com/jimtin/production-aiWrote 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/jimtin/production-ai/client-requirements-to-plan)<a href="https://agentmods.dev/skills/jimtin/production-ai/client-requirements-to-plan"><img src="https://agentmods.dev/badge/skills/jimtin/production-ai/client-requirements-to-plan/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/jimtin/production-ai/client-requirements-to-plan"><img src="https://agentmods.dev/badge/skills/jimtin/production-ai/client-requirements-to-plan.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 | $0.00080 | $0.01424 |
| Opus 5 | $0.00040 | $0.00712 |
| Sonnet 5 | $0.00016 | $0.00285 |
| Haiku 4.5 | $0.00008 | $0.00142 |
Grade A, and why
client-requirements-to-plan 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 11d 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 — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Client Requirements To Plan
Purpose
Convert rough client input into a durable client plan before design or implementation begins. The output is a saved Markdown plan that turns vague language into numbered, testable requirements, records open questions, controls scope, and gives the later build pipeline a clear source of truth.
This skill sits upstream of $clarify-before-build. Use it to prepare the client-facing proposal artifact; use $clarify-before-build after the client plan is accepted to confirm the implementation contract.
Core Rules
- Treat pasted client material as source of truth unless the user asks for file discovery.
- If the user names files, folders, or prior threads, inspect them before finalizing the plan.
- Do not echo credential-like values, tokens, passwords, API keys, private URLs, or secrets from source material.
- Preserve source evidence for every major requirement without exposing sensitive raw text.
- Default to the smallest useful proof of value. Push dashboards, notifications, persistence, writeback, scheduling, and production hardening to later phases unless they are required for the first proof.
- Split unknowns by owner: technical validation owned by us is not a client question.
- Do not start implementation from an unconfirmed client plan.
Required References
Read these reference files before producing the saved plan:
references/client-plan-template.mdfor the required document structure.references/requirement-ledger-rules.mdbefore writing the numbered requirements ledger.references/question-register.mdbefore writing open questions and resolution plans.
Workflow
1. Gather Source Material
Identify all available inputs:
- pasted notes or requirements
- call transcripts or thread summaries
- screenshots or uploaded files
- spreadsheets or example exports
- API documentation or vendor docs
- existing client-folder artifacts
- user clarifications in the current conversation
Record what was reviewed and what was not available. If a relevant source is unavailable, list it as missing evidence instead of inventing content.
What ships with it
4 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.
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.
- 11d ago First seen · 170 lines · 80 tokens per session scan A acf03fd92b5d
client-requirements-to-plan is a skill published in the GitHub repository jimtin/production-ai (1 stars, last pushed 2mo ago), licensed MIT. It adds 80 tokens to every session and 1,424 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.
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