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 agentmods add commands/infopibe/everything-claude-code/plangit clone --depth 1 https://github.com/Infopibe/everything-claude-codeWhat 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 | $0.00006 | $0.00279 |
| Opus 5 | $0.00003 | $0.00139 |
| Sonnet 5 | $0.00001 | $0.00056 |
| Haiku 4.5 | $0.00001 | $0.00028 |
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 2d 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.
This is a copy
100% identical to plan — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Plan Command
Create a detailed implementation plan for: $ARGUMENTS
Your Task
- Restate Requirements - Clarify what needs to be built
- Identify Risks - Surface potential issues, blockers, and dependencies
- Create Step Plan - Break down implementation into phases
- Wait for Confirmation - MUST receive user approval before proceeding
Output Format
Requirements Restatement
[Clear, concise restatement of what will be built]
Implementation Phases
[Phase 1: Description]
- Step 1.1
- Step 1.2 ...
[Phase 2: Description]
- Step 2.1
- Step 2.2 ...
Dependencies
[List external dependencies, APIs, services needed]
Risks
- HIGH: [Critical risks that could block implementation]
- MEDIUM: [Moderate risks to address]
- LOW: [Minor concerns]
Estimated Complexity
[HIGH/MEDIUM/LOW with time estimates]
WAITING FOR CONFIRMATION: Proceed with this plan? (yes/no/modify)
CRITICAL: Do NOT write any code until the user explicitly confirms with "yes", "proceed", or similar affirmative response.
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.
- 2d ago First seen · 50 lines · 6 tokens per session scan A 27d67051945d
plan is a command published in the GitHub repository Infopibe/everything-claude-code (8 stars, last pushed 5mo ago), licensed MIT. It adds 6 tokens to every session and 279 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to plan, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.