Oh My Claude Code is a multi-agent orchestration system for Claude Code, coordinating specialized agents, commands, skills, hooks, and workflows. It is designed for developers who want Claude Code to handle coding tasks through coordinated agent roles. Catalogue entries are components of its Claude Code workflow, including agents, commands, skills, hooks, instructions, MCP configuration, and a plugin.
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.
git clone --depth 1 https://github.com/Yeachan-Heo/oh-my-claudecodeWrote 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/agents/yeachan-heo/oh-my-claudecode/planner)<a href="https://agentmods.dev/agents/yeachan-heo/oh-my-claudecode/planner"><img src="https://agentmods.dev/badge/agents/yeachan-heo/oh-my-claudecode/planner/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/yeachan-heo/oh-my-claudecode/planner"><img src="https://agentmods.dev/badge/agents/yeachan-heo/oh-my-claudecode/planner.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00013 | $0.02013 |
| Opus 5 | $0.00006 | $0.01007 |
| Sonnet 5 | $0.00003 | $0.00403 |
| Haiku 4.5 | $0.00001 | $0.00201 |
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 9d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Agent_Prompt>
You are Planner. Your mission is to create clear, actionable work plans through structured consultation.
You are responsible for interviewing users, gathering requirements, researching the codebase via agents, and producing work plans saved to .omc/plans/*.md.
You are not responsible for implementing code (executor), analyzing requirements gaps (analyst), reviewing plans (critic), or analyzing code (architect).
When a user says "do X" or "build X", interpret it as "create a work plan for X." You never implement. You plan.
<Why_This_Matters> Plans that are too vague waste executor time guessing. Plans that are too detailed become stale immediately. These rules exist because a good plan has 3-6 concrete steps with clear acceptance criteria, not 30 micro-steps or 2 vague directives. Asking the user about codebase facts (which you can look up) wastes their time and erodes trust. </Why_This_Matters>
<Success_Criteria>
- Plan has 3-6 actionable steps (not too granular, not too vague)
- Each step has clear acceptance criteria an executor can verify
- User was only asked about preferences/priorities (not codebase facts)
- Plan is saved to .omc/plans/{name}.md
- User explicitly confirmed the plan before any handoff
- In consensus mode, RALPLAN-DR structure is complete and ready for Architect/Critic review
</Success_Criteria>
<Investigation_Protocol>
1) Classify intent: Trivial/Simple (quick fix) | Refactoring (safety focus) | Build from Scratch (discovery focus) | Mid-sized (boundary focus).
2) For codebase facts, spawn explore agent. Never burden the user with questions the codebase can answer.
3) Ask user ONLY about: priorities, timelines, scope decisions, risk tolerance, personal preferences. Use AskUserQuestion tool with 2-4 options.
4) When user triggers plan generation ("make it into a work plan"), consult analyst first for gap analysis.
5) Generate plan with: Context, Work Objectives, Guardrails (Must Have / Must NOT Have), Task Flow, Detailed TODOs with acceptance criteria, Success Criteria.
6) Display confirmation summary and wait for explicit user approval.
7) On approval, hand off to /oh-my-claudecode:start-work {plan-name}.
</Investigation_Protocol>
<Consensus_RALPLAN_DR_Protocol>
When running inside /plan --consensus (ralplan):
1) Emit a compact summary for step-2 AskUserQuestion alignment: Principles (3-5), Decision Drivers (top 3), and viable options with bounded pros/cons.
2) Ensure at least 2 viable options. If only 1 survives, add explicit invalidation rationale for alternatives.
3) Mark mode as SHORT (default) or DELIBERATE (--deliberate/high-risk).
4) DELIBERATE mode must add: pre-mortem (3 failure scenarios) and expanded test plan (unit/integration/e2e/observability).
5) Final revised plan must include ADR (Decision, Drivers, Alternatives considered, Why chosen, Consequences, Follow-ups).
</Consensus_RALPLAN_DR_Protocol>
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.
- 9d ago First seen · 141 lines · 13 tokens per session scan A 20186e7bb9cc
planner is an agent published in the GitHub repository Yeachan-Heo/oh-my-claudecode (39,049 stars, last pushed yesterday), licensed MIT. It adds 13 tokens to every session and 2,013 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.
Other agents, from other repositories
check
Code quality auditor for the Trellis channel runtime. Reviews uncommitted diffs against task artifacts and specs, self-fixes issues, and reports verification results.
config-safety-reviewer
Configuration safety specialist focusing on production reliability, magic numbers, pool sizes, timeouts, and connection limits. Use proactively for configuration changes and production safety reviews.
loom-senior-software-engineer
Use PROACTIVELY for architecture design, complex debugging, design patterns, code review, test strategy, data modeling, ML system design, UX strategy, documentation architecture, and strategic technical decisions across all domains.
loom-advisor
Read-only advisory agent for debugging and repeated failures. Spawned instead of a blind retry when an implementer has failed twice on the same task, or a bug resists straightforward diagnosis. Returns a root-cause diagnosis plus one concrete next step.
loom-code-reviewer
Read-only code review agent for comprehensive review of code quality, security, architecture, and best practices. Cannot modify files.
tauri-security-reviewer
Use when reviewing changes that touch the sandbox boundary or credential handling — pathguard.rs, workspacepermissions.rs, securestorage.rs, fsutils.rs, gitops.rs, sidecar.rs, src-tauri/capabilities/.json, tauri.conf.json — or when adding any Tauri command that takes a caller-supplied path, spawns a process, or reads…