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/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/smart-ai-memory/attune-ai/plan"><img src="https://agentmods.dev/badge/skills/smart-ai-memory/attune-ai/plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 119 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 5.5 | $0.00002 | $0.00365 |
| Sonnet 5.5 | $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 1mo 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.
- 1mo 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 5.5. 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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