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 skills/bananasjim/openplan-skill/openplan-gardennpx skills add BANANASJIM/openplan-skill --skill openplan-gardengit clone --depth 1 https://github.com/BANANASJIM/openplan-skillWrote 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/skills/bananasjim/openplan-skill/openplan-garden)<a href="https://agentmods.dev/skills/bananasjim/openplan-skill/openplan-garden"><img src="https://agentmods.dev/badge/skills/bananasjim/openplan-skill/openplan-garden.svg" alt="Measured on agentmods" 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 | $0.00108 | $0.00827 |
| Opus 5 | $0.00054 | $0.00413 |
| Sonnet 5 | $0.00022 | $0.00165 |
| Haiku 4.5 | $0.00011 | $0.00083 |
Grade A, and why
openplan-garden 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 6d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenPlan Garden
Use this after $openplan-core for document quality, periodic documentation maintenance, and semantic drift inspection. Garden is about preserving the clarity of human goal/intent over time.
Core Rule
Garden first reports. It does not rewrite durable docs or memory unless the user explicitly asks for a cleanup/edit pass.
What Garden Checks
- Goal/intent clarity: can a future human or agent tell why this exists?
- Authority clarity: is this source of truth, draft, handoff, review, or temporary brief?
- Layer clarity: does it mix goal/intent, design, spec, implementation, and review without labels?
- Rationale: are decisions explained, not just stated?
- Staleness: are time-sensitive or superseded claims marked?
- Duplication: is content copied where a reference would work?
- Traceability: are important claims tied to sources or evidence?
- Zero-context readability: can a competent reader understand it without the chat?
- Human-decision boundary: does it record human decisions separately from agent suggestions?
- Next-action clarity: does it say what should happen next, if anything?
Periodic Garden Pass
Use garden as the periodic documentation cleanup workflow. A periodic pass checks:
- stale or superseded documents;
- duplicated rationale that should become references;
- missing or unclear authority labels;
- memory/docs conflicts;
- abandoned TODOs or unresolved questions;
- research/review/handoff artifacts that should be archived, promoted, or left alone;
- docs that no longer pass zero-context comprehension.
Garden first reports proposed cleanup. It may edit only when the user explicitly asks for a cleanup pass, and durable goal/intent changes still require $openplan-record and human confirmation through the human-facing coordinator.
Workflow
- Identify document type: memory, design, decision, spec, handoff, review, tutorial, temporary brief.
- Identify the docs root when a whole documentation surface is being reviewed.
- Load only the document and directly referenced context needed to judge it.
- Run optional deterministic checks if available and safe.
- Apply
references/checklist.md. - Report findings using
references/report-contract.md. - If the user requests cleanup, use
$openplan-recordbefore editing durable memory/docs. - For periodic maintenance, separate safe mechanical cleanup from human-owned meaning changes.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 6d ago First seen · 77 lines · 108 tokens per session scan A 395b87723db3
openplan-garden is a skill published in the GitHub repository BANANASJIM/openplan-skill (4 stars, last pushed 3mo ago), licensed MIT. It adds 108 tokens to every session and 827 once invoked, about $0.0005 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 2026-08-31.
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