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 skills/jnarowski/agentcmd/planningnpx skills add jnarowski/agentcmd --skill planninggit clone --depth 1 https://github.com/jnarowski/agentcmdWhat 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 | $0.00045 | $0.01308 |
| Opus 5 | $0.00023 | $0.00654 |
| Sonnet 5 | $0.00009 | $0.00262 |
| Haiku 4.5 | $0.00005 | $0.00131 |
Grade A, and why
planning 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 today.
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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planning Skill
Overview
This skill provides comprehensive planning workflows for features and system changes. It focuses on the research and clarification phase - gathering context, exploring architecture, and asking good questions before spec generation.
When to Use This Skill
Use this skill when:
- In planning/plan mode (auto-trigger if possible)
- User says: "plan this", "research this feature", "help me understand"
- User asks: "what do I need to know before implementing X?"
- Before generating specs with
/cmd:generate-spec - Need to explore codebase patterns and architecture
Core Workflow
1. Research Phase
- Explore codebase for similar existing features
- Identify which domain/area this belongs in
- Locate related types, schemas, services, routes
- Check test patterns in relevant areas
- Review database models (if applicable)
- Use
references/research-checklist.mdfor systematic exploration
2. Context Gathering
- Internal docs: Check
.agent/docs/for relevant patterns - CLAUDE.md: Review project conventions and rules
- context7 MCP (if available): Fetch external library docs
- Check for
mcp__context7__*tools - Use for React, Fastify, Prisma, etc. documentation
- Fall back to WebFetch/WebSearch if not available
- Check for
- See
references/context-sources.mdfor detailed guidance
3. Clarification (If Needed)
Ask clarifying questions ONE AT A TIME if implementation approach is unclear:
- Don't use the Question tool
- Use this template:
**Question**: [Your question] **Suggestions**: 1. [Option 1] (recommended - why) 2. [Option 2] 3. Other - user specifies - See
references/clarification-questions.mdfor examples and templates
4. Complexity Assessment
- Estimate file count and scope
- Identify cross-cutting concerns
- Assess if new patterns needed or extending existing
- Determine context requirements for implementation
- Flag if complexity suggests breaking into smaller features
- See
references/complexity-assessment.mdfor detailed rubric
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- today First seen · 149 lines · 45 tokens per session scan A 022bc70794be
planning is a skill published in the GitHub repository jnarowski/agentcmd (18 stars, last pushed 8mo ago), licensed MIT. It adds 45 tokens to every session and 1,308 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 2026-09-01.
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