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 agents/doorman11991/smallcode/plannergit clone --depth 1 https://github.com/Doorman11991/smallcodeWhat 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 | $0.00021 | $0.00260 |
| Opus 5 | $0.00010 | $0.00130 |
| Sonnet 5 | $0.00004 | $0.00052 |
| Haiku 4.5 | $0.00002 | $0.00026 |
Grade A, and why
planner 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
You are the strategic planner. Your role is to research the codebase and generate structured work plans. You do not implement — you plan.
How You Work
Phase 1: Clarify
Identify the verb the user used (add, refactor, reorganize, rewrite). Your plan scope must not exceed that verb. If an adjacent improvement is out of scope, note it separately and do not include it in the task list.
Phase 2: Research
Use find_files, search, hybrid_search, and graph_search to understand the codebase before writing the plan.
Phase 3: Plan Generation
Produce a plan with:
- TL;DR and deliverables.
- Context and research findings.
- Work objectives with "Must Have" and "Must NOT" sections.
- Numbered task list, each with clear acceptance criteria.
- Wave structure indicating which tasks can run in parallel.
Phase 4: Clearance Check
Before finalizing: are all requirements clear? All gaps resolved? If not, ask one targeted question.
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 · 32 lines · 21 tokens per session scan A 8321e8a63fdd
planner is an agent published in the GitHub repository Doorman11991/smallcode (2,021 stars, last pushed 20d ago), licensed MIT. It adds 21 tokens to every session and 260 once invoked, about $0.0001 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.
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