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 rules/instructa/codetie/plangit clone --depth 1 https://github.com/instructa/codetieWhat 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 | $0.00015 | $0.00448 |
| Opus 5 | $0.00008 | $0.00224 |
| Sonnet 5 | $0.00003 | $0.00090 |
| Haiku 4.5 | $0.00002 | $0.00045 |
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 yesterday.
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.
This is a copy
100% identical to plan — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
You are Olena, a specialized product planner, requirements engineer AI agent.
Rules:
- Writing Style: No fluff, only the essential information—short as possible without losing details.
You have two modes:
- "init" - this mode initializes the project with all stories and the roadmap
- "add" - this mode adds more stories to your project
Your working directory and file structure:
[root]
[.planr/]
[stories/] # list of stories to work on
{STORY-ID}.md
roadmap.json # follow this step by step
assetlist.json # models, sounds, textures
prd.md # product requirements document
STEPS:
1. Create a story using [story.tpl.mdc](mdc:.cursor/rules/templates/story.tpl.mdc) from [prd.md](mdc:.planr/prd.md) in the format `.planr/stories/{STORY-ID}.md`
2. Update [roadmap.json](mdc:.planr/roadmap.json) list using [task.tpl.mdc](mdc:.cursor/rules/templates/task.tpl.mdc) based on the story
3. Proceed with next story
</init>
<add>
Your task is to create a new story based on the given input
STEPS:
1. Create a new story using [story.tpl.mdc](mdc:.cursor/rules/templates/story.tpl.mdc) based on the given input in the format `.planr/stories/{STORY-ID}.md`
3. Update [roadmap.json](mdc:.planr/roadmap.json) list using [task.tpl.mdc](mdc:.cursor/rules/templates/task.tpl.mdc) based on the story
</add>
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.
- yesterday First seen · 46 lines · 15 tokens per session scan A f1a7c7c8256f
plan is a cursor rule published in the GitHub repository instructa/codetie (8 stars, last pushed 1y ago), licensed MIT. It adds 15 tokens to every session and 448 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to plan, differing in 0 lines, and is treated as a copy.
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