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/liortesta/clawdagent/plangit clone --depth 1 https://github.com/liortesta/ClawdAgentWhat 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 | $0.00000 | $0.00357 |
| Opus 5 | $0.00000 | $0.00179 |
| Sonnet 5 | $0.00000 | $0.00071 |
| Haiku 4.5 | $0.00000 | $0.00036 |
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.
What it actually says
Strategic Planning
Before writing ANY code, create a detailed plan with multi-agent input.
Process:
- Understand: Read the requirement carefully. Ask clarifying questions if anything is ambiguous.
- CTO Review: Use the CTO agent to evaluate the overall approach — is this the right direction?
- Architecture Design: Use the architect agent to design the solution — modules, interfaces, data model
- Break Down: Split into tasks with clear dependencies
- Estimate Complexity: Rate each task (S/M/L/XL)
- Risk Assessment: Identify risks and mitigation strategies
- Present Plan: Show the complete plan for user approval
Plan Template:
## Plan: [Feature/Task Name]
### Goal
[1-2 sentences: what we're building and why]
### Approach
[CTO-approved approach with rationale]
### Architecture
[Architect-designed structure]
### Tasks
| # | Task | Size | Depends On | Files |
|---|------|------|-----------|-------|
| 1 | ... | S | - | file1.ts |
| 2 | ... | M | 1 | file2.ts, file3.ts |
### Risks
- [Risk 1]: [Mitigation]
- [Risk 2]: [Mitigation]
### Verification
- [ ] [How to verify task 1]
- [ ] [How to verify task 2]
- [ ] [Final integration test]
Rules:
- NEVER start coding before the plan is approved
- ALWAYS get CTO input for tasks touching >5 files
- ALWAYS include verification steps — "how do we know it works?"
$ARGUMENTS
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 · 49 lines · 0 tokens per session scan A 48ee004a48b8
plan is a command published in the GitHub repository liortesta/ClawdAgent (11 stars, last pushed 5d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 357 tokens. 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.
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.