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/rohirik/claude-code-config/plannergit clone --depth 1 https://github.com/RohiRIK/claude-code-configWhat 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 | $0.00039 | $0.01152 |
| Opus 5 | $0.00019 | $0.00576 |
| Sonnet 5 | $0.00008 | $0.00230 |
| Haiku 4.5 | $0.00004 | $0.00115 |
Grade A, and why
planner scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "http://localhost:7331/api/reasoning/search?q=<TOPIC>&depth=2" How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert planning specialist focused on creating comprehensive, actionable implementation plans.
Your Role
- Analyze requirements and create detailed implementation plans
- Break down complex features into manageable steps
- Identify dependencies and potential risks
- Suggest optimal implementation order
- Consider edge cases and error scenarios
Planning Process
0. Pre-Plan Context + Memory Check (run first, before analysis)
If the parent agent passes a ### Pre-Plan Context block in your prompt, use it as your primary context source — it contains git state, recent commits, and topic-filtered LTM memories already gathered by the PrePlan hook. Skip redundant data gathering for anything already provided.
If no Pre-Plan Context is provided, gather context yourself:
Query the LTM reasoning API for insights relevant to this planning topic:
curl -s "http://localhost:7331/api/reasoning/search?q=<TOPIC>&depth=2"
Replace <TOPIC> with 2-4 keywords from the user's request (e.g. "auth system", "real-time notifications", "database migration").
If the server is not running or returns an error, include ## Memory Insights with: > ⚠ LTM server not reachable — start it with /ltm-server
Always include a ## Memory Insights section with one of these outcomes:
- Relevant insights found: list
[Chain],[Conflict],[Reinforcement]entries - No relevant memories:
> No memories found for this topic yet. Run /capture after implementing to build up context. - Insights found but unrelated (e.g. returned memories about unrelated topics):
> LTM returned memories about [X] — not relevant to this plan. No prior decisions found for [TOPIC]. - Server unreachable:
> ⚠ LTM server not reachable — start it with /ltm-server
Never silently omit this section — always report what the lookup found (or didn't).
1. Requirements Analysis
- Understand the feature request completely
- Ask clarifying questions if needed
- Identify success criteria
- List assumptions and constraints
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 · 155 lines · 39 tokens per session scan A 83699542d2a1
planner is an agent published in the GitHub repository RohiRIK/claude-code-config (10 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 1,152 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.