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/yunbow/ai-dev-os-plugin-cursor/ai-dev-os-ticketgit clone --depth 1 https://github.com/yunbow/ai-dev-os-plugin-cursorWrote 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/rules/yunbow/ai-dev-os-plugin-cursor/ai-dev-os-ticket)<a href="https://agentmods.dev/rules/yunbow/ai-dev-os-plugin-cursor/ai-dev-os-ticket"><img src="https://agentmods.dev/badge/rules/yunbow/ai-dev-os-plugin-cursor/ai-dev-os-ticket.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 | $0.00032 | $0.00332 |
| Opus 5 | $0.00016 | $0.00166 |
| Sonnet 5 | $0.00006 | $0.00066 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
ai-dev-os-ticket 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 3d 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
AI Dev OS Ticket Generation
Execution Flow
1. Analyze the Request
Parse the user's request and identify the implementation goal.
2. Identify Affected Files
Search the codebase to determine files that will be modified, created, or deleted.
3. Parse .cursorrules and Load Guidelines
Extract guideline file paths and read them to understand active rules.
4. Build Dynamic Mapping
Map affected files to their relevant guidelines using file pattern matching.
5. Extract Checklist Items
From the mapped guidelines, extract items relevant to this ticket.
6. Determine Output Destination
Ask the user:
- Local file: Create
TICKET-NNN-slug.mdin the project - GitHub Issue: Use
gh issue create
7. Present Preview
## Ticket Preview
### Title
> [Concise title]
### Description
[What needs to be done and why]
### Implementation Summary
| Action | File | Description |
|--------|------|-------------|
### Guideline Checklist
- [ ] [Rule from guideline-file.md]
- [ ] [Rule from guideline-file.md]
### Acceptance Criteria
1. ...
8. Create Ticket
Create the ticket in the chosen format after user approval.
Language
Respond in the same language as the project's .cursorrules file.
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.
- 3d ago First seen · 60 lines · 32 tokens per session scan A 0f831ba8d3d0
ai-dev-os-ticket is a cursor rule published in the GitHub repository yunbow/ai-dev-os-plugin-cursor (2 stars, last pushed 5mo ago), licensed MIT. It adds 32 tokens to every session and 332 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 2026-08-31.
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