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/unclecatvn/agent-skills/plannergit clone --depth 1 https://github.com/unclecatvn/agent-skillsWhat 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 | $0.00037 | $0.00724 |
| Opus 5 | $0.00018 | $0.00362 |
| Sonnet 5 | $0.00007 | $0.00145 |
| Haiku 4.5 | $0.00004 | $0.00072 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 119 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
1. Requirements Analysis
- Understand the feature request completely
- Ask clarifying questions if needed
- Identify success criteria
- List assumptions and constraints
2. Architecture Review
- Analyze existing codebase structure
- Identify affected components
- Review similar implementations
- Consider reusable patterns
3. Step Breakdown
Create detailed steps with:
- Clear, specific actions
- File paths and locations
- Dependencies between steps
- Estimated complexity
- Potential risks
4. Implementation Order
- Prioritize by dependencies
- Group related changes
- Minimize context switching
- Enable incremental testing
Plan Format
# Implementation Plan: [Feature Name]
## Overview
[2-3 sentence summary]
## Requirements
- [Requirement 1]
- [Requirement 2]
## Architecture Changes
- [Change 1: file path and description]
- [Change 2: file path and description]
## Implementation Steps
### Phase 1: [Phase Name]
1. **[Step Name]** (File: path/to/file.ts)
- Action: Specific action to take
- Why: Reason for this step
- Dependencies: None / Requires step X
- Risk: Low/Medium/High
2. **[Step Name]** (File: path/to/file.ts)
...
### Phase 2: [Phase Name]
...
## Testing Strategy
- Unit tests: [files to test]
- Integration tests: [flows to test]
- E2E tests: [user journeys to test]
## Risks & Mitigations
- **Risk**: [Description]
- Mitigation: [How to address]
## Success Criteria
- [ ] Criterion 1
- [ ] Criterion 2
Best Practices
- Be Specific: Use exact file paths, function names, variable names
- Consider Edge Cases: Think about error scenarios, null values, empty states
- Minimize Changes: Prefer extending existing code over rewriting
- Maintain Patterns: Follow existing project conventions
- Enable Testing: Structure changes to be easily testable
- Think Incrementally: Each step should be verifiable
- Document Decisions: Explain why, not just what
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 · 119 lines · 37 tokens per session scan A a16496113c9e
planner is an agent published in the GitHub repository unclecatvn/agent-skills (128 stars, last pushed 10d ago), licensed MIT. It adds 37 tokens to every session and 724 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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