Borrowing it
Nothing to install: this file belongs to Smart-AI-Memory/attune-ai. 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/Smart-AI-Memory/attune-ai/main/.agents/skills/plan/SKILL.mdgit clone --depth 1 https://github.com/Smart-AI-Memory/attune-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/smart-ai-memory/attune-ai/plan)<a href="https://agentmods.dev/skills/smart-ai-memory/attune-ai/plan"><img src="https://agentmods.dev/badge/skills/smart-ai-memory/attune-ai/plan.svg" alt="Measured on agentmods" 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 | $0.00006 | $0.00913 |
| Opus 5 | $0.00003 | $0.00456 |
| Sonnet 5 | $0.00001 | $0.00183 |
| Haiku 4.5 | $0.00001 | $0.00091 |
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 6d 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 — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
plan
Development planning and architecture design.
Routes
| Subcommand | Action |
|---|---|
feature |
Plan a new feature |
refactor |
Plan refactoring |
architecture |
Architecture review |
Usage
/plan # Ask what to plan
/plan feature # Plan a feature
/plan refactor # Plan refactoring
/plan architecture # Architecture review
Behavior
All planning tasks use EnterPlanMode to create
a structured plan for user approval before any
implementation.
After every plan is approved, follow the Post-Plan Handoff process.
feature
Use AskUserQuestion to understand:
- What feature? What problem does it solve?
- What's the scope? Which files/modules?
- Any constraints or preferences?
Then use EnterPlanMode to design the implementation
plan. After approval, follow Post-Plan Handoff.
refactor
Use AskUserQuestion to understand:
- What code needs refactoring?
- What's the goal? (simplify, split, extract)
- Any constraints?
Then use EnterPlanMode to plan the refactoring.
After approval, follow Post-Plan Handoff.
architecture
Use AskUserQuestion to understand:
- What system or subsystem to review?
- Any specific concerns?
Then analyze the codebase structure and provide architectural recommendations. If the review produces actionable changes, follow Post-Plan Handoff.
Post-Plan Handoff
This section applies to ALL routes after a plan is approved.
Step 1: Save the plan
Save the approved plan to .claude/plans/ using
the Plan File Format below.
File naming convention:
{route}-{slug}-{YYYY-MM-DD}.md
Examples:
refactor-auth-module-2026-02-22.mdfeature-dark-mode-2026-02-22.md
Ensure .claude/plans/ directory exists before
writing.
Step 2: Offer execution
Use AskUserQuestion to ask:
question: "Plan saved to .claude/plans/{filename}.
Ready to execute?"
header: "Next"
options:
- label: "Execute now"
description: "Start implementing — I'll carry
the plan context forward so you won't need
to re-explain anything"
- label: "Save for later"
description: "Plan is saved — pick it up later
with /dev {route}"
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.
- 6d ago First seen · 171 lines · 6 tokens per session scan A e0e0baa88a4f
plan is a skill published in the GitHub repository Smart-AI-Memory/attune-ai (10 stars, last pushed today), licensed Apache-2.0. It adds 6 tokens to every session and 913 once invoked, about $0.0000 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
eco-max
Maximum-savings variant of /eco - the same frugality rules PLUS a low reasoning-effort override for the invoked task. Use for routine chores (rename, small fix, quick question, boilerplate) when the user wants absolute minimum token spend; prefer plain /eco for hard or high-stakes work. Works in any language.
wiki-ingest
Ingest a source into the project wiki as OKF v0.2 markdown. Point at a file, PR, or doc and the wiki-curator extracts knowledge, writes YAML frontmatter, and updates relevant concept pages.
wiki-lint
Health-check the project wiki for OKF v0.2 conformance — missing frontmatter, missing type:, malformed index.md/log.md, stale pages past staleafter, broken cross-references, and coverage gaps.
run
Run a full pipeline for a task. Orchestrates roles through stages (standalone or HOTL-integrated).
ci-repair
Fix CI failures by fetching GitHub Actions logs, dispatching dev to fix, verifying locally, and pushing.
deepdive
Full specialist analysis via parallel agent dispatch. Researcher, Architect, and PM produce a prioritized report of what to build next (30-60s).