Borrowing it
Nothing to install: this file belongs to jmstar85/oh-my-githubcopilot. 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/jmstar85/oh-my-githubcopilot/main/.github/skills/plan/SKILL.mdgit clone --depth 1 https://github.com/jmstar85/oh-my-githubcopilotWrote 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/jmstar85/oh-my-githubcopilot/plan)<a href="https://agentmods.dev/skills/jmstar85/oh-my-githubcopilot/plan"><img src="https://agentmods.dev/badge/skills/jmstar85/oh-my-githubcopilot/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/jmstar85/oh-my-githubcopilot/plan"><img src="https://agentmods.dev/badge/skills/jmstar85/oh-my-githubcopilot/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 | $0.00033 | $0.01034 |
| Opus 5.5 | $0.00013 | $0.00414 |
| Sonnet 5.5 | $0.00007 | $0.00207 |
| Haiku 4.5 | $0.00003 | $0.00103 |
Grade A, and why
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 2mo 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan
Creates comprehensive, actionable work plans through intelligent interaction. Auto-detects whether to interview (broad requests) or plan directly (detailed requests).
Modes
| Mode | Trigger | Behavior |
|---|---|---|
| Interview | Default for broad requests | Interactive requirements gathering |
| Direct | --direct, or detailed request |
Skip interview, generate plan directly |
| Consensus | --consensus, "ralplan" |
Planner → Architect → Critic loop |
| Review | --review |
Critic evaluation of existing plan |
Interactive Hook Protocol
MANDATORY: Use vscode_askQuestions for ALL user-facing decision points in this skill (when available).
If vscode_askQuestions is NOT available (e.g., Copilot CLI), present numbered options in markdown and ask the user to respond with a number or freeform text.
When to Fire Hooks
| Trigger Point | Question Type |
|---|---|
| Interview mode: each question round | Scope/preference/constraint question with options |
| Interview mode: readiness check | "Ready to generate plan?" gate |
| Consensus mode: plan trade-offs | Present design options with pros/cons |
| Consensus mode: critic rejection | Show rejection reasons, ask for direction |
| All modes: plan approval | Final plan review before execution |
Interview Mode (broad/vague requests)
- Classify request: broad triggers interview
- HOOK: Ask ONE focused question via
vscode_askQuestionsfor preferences, scope, constraints- Provide 3-5 contextual options derived from codebase analysis
- Always include freeform input (
allowFreeformInput: true)
- Gather codebase facts via @explore BEFORE asking user
- Consult @analyst for hidden requirements
- HOOK: Readiness gate — ask user if ready to generate plan:
header: "plan-readiness" question: "I've gathered enough context. Ready to generate the plan?" options: [ { label: "Yes, generate the plan", recommended: true }, { label: "I have more requirements to add" }, { label: "Show me what you've gathered so far" } ] - Create plan when user signals readiness
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.
- 2mo ago First seen · 110 lines · 33 tokens per session scan A d673a79f596b
plan is a skill published in the GitHub repository jmstar85/oh-my-githubcopilot (162 stars, last pushed 5mo ago), licensed MIT. It adds 33 tokens to every session and 1,034 once invoked, about $0.0001 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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