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/othmanadi/planning-with-files/plan-loopgit clone --depth 1 https://github.com/OthmanAdi/planning-with-filesWhat 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 | $0.00040 | $0.00490 |
| Opus 5 | $0.00020 | $0.00245 |
| Sonnet 5 | $0.00008 | $0.00098 |
| Haiku 4.5 | $0.00004 | $0.00049 |
Grade A, and why
plan-loop scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Run a planning-aware cadence on top of Claude Code's /loop primitive.
Steps:
- Parse args:
- First arg matching
^\d+[smhd]$is the interval (default10m). - Remaining args are an optional task prompt.
- First arg matching
- Resolve the active plan as in
/plan-attest. - Compose the loop prompt:
- If user passed a task prompt: use it verbatim.
- Else: use the default planning tick prompt:
Read task_plan.md and progress.md. Run scripts/check-complete.sh to see remaining phases. If no progress.md entry has been added since the last loop tick, write one summarizing the current state. If a phase finished, update its Status: line in task_plan.md. Continue the next phase if work remains.
- Invoke
/loop <interval> <prompt>. - Confirm to the user: print the interval, the active plan ID, and remind that bare
/loopinvocation alone (without args) runs Claude Code's built-in maintenance prompt —/plan-loopdiffers by always grounding the tick in the planning files.
If task_plan.md does not exist, refuse and direct user to run /plan first.
Why this exists:
/loop runs prompts on cron without any plan-state contract. /plan-loop injects a plan-aware default so the recurring tick always re-reads the planning files first, runs the completion check, and writes a progress entry. Users get "babysit my plan" UX without writing a custom loop prompt.
Notes:
/plan-loopcomposes with/loop; it does not replace it./loop 5m "anything"still works.- For "babysit until plan is done" semantics: combine
/plan-loop 10m(cadence) with/plan-goal(termination criterion). The loop runs every 10 minutes; the goal stops the loop when the plan is complete. - The default tick prompt is intentionally short so it stays within compaction-safe length.
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 · 38 lines · 40 tokens per session scan A e0d99651190e
plan-loop is a command published in the GitHub repository OthmanAdi/planning-with-files (26,563 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 490 once invoked, about $0.0002 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 2026-08-30.
Other commands, from other repositories
BOOTSTRAP
First-run ritual for new agents.
UPDATE_MEMORY
Time to organize your memory.
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.