Borrowing it
Nothing to install: this file belongs to mrlarson2007/copilot-tdd-harness. 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/mrlarson2007/copilot-tdd-harness/master/.github/skills/requirements-planning/SKILL.mdgit clone --depth 1 https://github.com/mrlarson2007/copilot-tdd-harnessWrote 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/mrlarson2007/copilot-tdd-harness/requirements-planning)<a href="https://agentmods.dev/skills/mrlarson2007/copilot-tdd-harness/requirements-planning"><img src="https://agentmods.dev/badge/skills/mrlarson2007/copilot-tdd-harness/requirements-planning/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/mrlarson2007/copilot-tdd-harness/requirements-planning"><img src="https://agentmods.dev/badge/skills/mrlarson2007/copilot-tdd-harness/requirements-planning.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 | $0.00022 | $0.00664 |
| Opus 5 | $0.00011 | $0.00332 |
| Sonnet 5 | $0.00004 | $0.00133 |
| Haiku 4.5 | $0.00002 | $0.00066 |
Grade A, and why
requirements-planning 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 10d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Requirements Planning Skill
Use this skill before development to help break down a broad or ambiguous requirement into concrete, testable behaviors.
This skill is for planning only. It should not write production code, write tests, or execute a RED -> GREEN cycle.
Purpose
Your audience is a software team that needs help breaking down a broad or ambiguous requirement into concrete, testable behaviors. The goal is to help the team think like a strong software engineer, QA, and requirements analyst using BDD and TDD principles to:
- clarify what the user actually wants
- identify candidate behaviors from a feature request
- outline edge cases
- outline key scenarios
- express each planned behavior as a Given, When, Then scenario
Interaction Model
This skill is interactive.
- The user provides the initial feature or behavior prompt.
- The skill helps the user refine that request into concrete scenarios.
- If the request is still ambiguous, ask exactly one focused clarification question and wait.
- Do not continue planning until the user answers the clarification question.
Clarification Rules
Stop and ask exactly one focused question when any of the following are true:
- the request names a feature area but not a specific behavior
- the request has multiple plausible interpretations or stakeholder outcomes
- the next Given, When, Then scenario would require guessing inputs, outputs, actors, or scope
Do not self-resolve ambiguity just because one option looks reasonable.
Required Output
When the request is clear enough, produce a requirements plan with these sections:
- feature summary
- stakeholders or affected users
- assumptions or open questions
- scenarios
Each scenario must:
- describe one externally visible behavior
- use explicit Given, When, Then formatting
- include happy path or edge case intent clearly enough to guide later implementation and testing
File Output
When the plan is ready, propose writing it to a markdown file under:
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.
- 10d ago First seen · 83 lines · 22 tokens per session scan A 129ef5a7d10a
requirements-planning is a skill published in the GitHub repository mrlarson2007/copilot-tdd-harness (5 stars, last pushed 3mo ago), licensed MIT. It adds 22 tokens to every session and 664 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 2026-08-31.
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