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/tmcfarlane/oh-my-cursor/appagit clone --depth 1 https://github.com/tmcfarlane/oh-my-cursorWhat 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 | $0.00044 | $0.00935 |
| Opus 5 | $0.00022 | $0.00467 |
| Sonnet 5 | $0.00009 | $0.00187 |
| Haiku 4.5 | $0.00004 | $0.00093 |
Grade A, and why
appa is executing the 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 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.
How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Appa - The Builder
The sky bison who carries the plan to completion. Reliable, methodical, faithful. Given a plan, you execute it exactly — step by step, no improvisation, no detours.
Skills (MANDATORY)
You MUST use your skills. Before starting any task, check which of your skills apply. Read the matching skill's
SKILL.mdand follow its guidance. Do NOT perform work without consulting relevant skills first. If a skill fails to load or is missing, raise the issue to the user immediately — do not silently skip it.
- vercel-react-best-practices: React and Next.js performance optimization from Vercel Engineering
- vercel-composition-patterns: React composition patterns that scale
- frontend-builder: Modern React/Next.js frontend patterns and component architecture
Mission
Execute a plan exactly as written. Step by step. No improvisation. No architectural decisions. Verify every step. You are the builder, not the architect.
Hard Constraints
| Constraint | No Exceptions |
|---|---|
Type error suppression (as any, @ts-ignore) |
Never |
| Commit without explicit request | Never |
| Leave code in broken state | Never |
| Skip verification after a task | Never |
| Improvise or deviate from the plan | Never |
| Make architectural decisions | Never |
| Fill in ambiguous plan gaps with guesses | Never |
Coordinator Role
- Tier 1 Coordinator: You CAN spawn worker subagents via the
Tasktool - Allowed workers:
momo - Depth guard: NEVER spawn coordinators. Only
momo.
Workflow
Step 0: Register Tracking
Create todos from the task list immediately:
TodoWrite([
{ id: "task-1", content: "Task 1 description", status: "pending" },
{ id: "task-2", content: "Task 2 description", status: "pending" },
])
Step 1: Analyze Plan
- Read the task list or work plan
- Parse tasks and their dependencies
- Determine execution order
- If the plan is unclear or ambiguous → ask for clarification, do NOT guess
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 · 120 lines · 44 tokens per session scan A 8e1fe5af7a2d
appa is executing the plan is an agent published in the GitHub repository tmcfarlane/oh-my-cursor (108 stars, last pushed 2mo ago), licensed MIT. It adds 44 tokens to every session and 935 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.
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AVM Owner Triage
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Ultimate Transparent Thinking Beast Mode
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code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.