Borrowing it
Nothing to install: this file belongs to llama-farm/llamafarm. 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/llama-farm/llamafarm/main/.agents/commands/plan.mdgit clone --depth 1 https://github.com/llama-farm/llamafarmWrote 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/commands/llama-farm/llamafarm/plan)<a href="https://agentmods.dev/commands/llama-farm/llamafarm/plan"><img src="https://agentmods.dev/badge/commands/llama-farm/llamafarm/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/commands/llama-farm/llamafarm/plan"><img src="https://agentmods.dev/badge/commands/llama-farm/llamafarm/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 | $0.00000 | $0.01141 |
| Opus 5.5 | $0.00000 | $0.00456 |
| Sonnet 5.5 | $0.00000 | $0.00228 |
| Haiku 4.5 | $0.00000 | $0.00114 |
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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Planning Playbook
Turn your completed research into a minimal, verifiable change plan. This document helps you define scope, sequence work, and specify how you’ll prove success before writing code.
Inputs
- The research note in
thoughts/shared/research/<issue_id>_<slug>.md - Clarifications from the user for any uncertainties identified in research
- Awareness of repo guidelines in
AGENTS.mdand project conventions - Answers to the “Known unknowns” listed in the research note (resolve with the user first)
Outputs
- A plan document at
thoughts/shared/plans/<issue_id>_<slug>-plan.mdthat includes:- Clear scope and acceptance criteria
- File-level change list and impact analysis
- Test and verification plan (commands you’ll run)
- Risk/rollout/rollback strategy
- Docs and config update plan
- Estimated effort and sequencing
Planning Workflow
- Confirm problem and success criteria from the research note.
- Identify impacted projects and targets (prefer workspace graph/tools when available).
- Map entry points and contracts to be changed; list interfaces/CLIs/APIs affected.
- Draft the smallest viable change list; postpone refactors.
- Define the test strategy and exact commands you will run to verify.
- Specify risk controls: flags, canaries, and rollback steps.
- List required updates to docs and configuration.
- Sequence tasks and add rough estimates; call out external dependencies.
- Share the plan; adjust based on feedback before coding.
Change List: plan by files and boundaries
For each change, capture:
- File(s)/Module(s): paths to create/edit/remove
- Change summary: what will be added/modified and why
- Contracts: CLI flags, API schemas, function signatures, data shapes
- Dependencies: services, tasks/targets, feature flags, migrations
- Blast radius: who calls this code; risks and mitigations
Example structure:
- server/api/items.py: add GET /items/{id} handler returning X schema
- server/services/items.py: implement fetch_item with validation Y
- cli/cmd/items.go: add `lf items get` to call server endpoint
- docs/website/...: add usage docs and examples
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 · 141 lines · 0 tokens per session scan A a0d7159ad7f2
plan is a command published in the GitHub repository llama-farm/llamafarm (836 stars, last pushed 4mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,141 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
model-config
Configure AI provider models for Claude Octopus workflows.
model-check
Reassess the current session and recommend the right model and effort level.
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.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.