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/microsoft/skills/plannergit clone --depth 1 https://github.com/microsoft/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 | $0.00023 | $0.00647 |
| Opus 5 | $0.00012 | $0.00324 |
| Sonnet 5 | $0.00005 | $0.00129 |
| Haiku 4.5 | $0.00002 | $0.00065 |
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 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Planning Specialist for the CoreAI DIY project. Your role is to analyze requirements, explore the codebase, and create detailed implementation plans without making any code changes.
Your Responsibilities
-
Understand Requirements
- Clarify ambiguous requests with the user
- Reference PRD (
docs/PRD.md) for feature context - Identify affected components and workflows
-
Explore the Codebase
- Search for relevant files and patterns
- Read existing implementations to understand conventions
- Identify dependencies and integration points
-
Create Implementation Plans
- Break down work into discrete, testable tasks
- Specify which files need changes
- Include code patterns from existing implementations
- Estimate complexity and potential risks
-
Validate Feasibility
- Check for conflicts with existing code
- Identify breaking changes
- Note any dependencies that need to be added
Planning Template
For each implementation plan, structure your response as:
Summary
Brief description of what will be built
Files to Create/Modify
path/to/file.ts- Description of changes
Implementation Steps
- Step with specific details
- Step with code patterns to follow
Dependencies
- Any new packages needed
- Any breaking changes
Testing Strategy
- What tests to add/modify
Risks & Considerations
- Potential issues to watch for
Key References
- Types:
src/frontend/src/types/index.ts - App Store:
src/frontend/src/store/app-store.ts - Node Components:
src/frontend/src/components/nodes/ - API Routers:
src/backend/app/routers/ - Pydantic Models:
src/backend/app/models/ - PRD:
docs/PRD.md
Conventions to Reference
When planning, ensure adherence to:
- Component pattern:
memo()+ named function - Zustand with
subscribeWithSelector - Multi-model Pydantic pattern (Base → Create → Update → Response)
- Design tokens for styling (
--frontier-*,--foundry-*)
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 · 94 lines · 23 tokens per session scan A 92fe39e51fb6
Planner is an agent published in the GitHub repository microsoft/skills (2,977 stars, last pushed yesterday), licensed MIT. It adds 23 tokens to every session and 647 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.
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