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 commands/vishnu2kmohan/mcp-server-langgraph/plan-featuregit clone --depth 1 https://github.com/vishnu2kmohan/mcp-server-langgraphWrote 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/commands/vishnu2kmohan/mcp-server-langgraph/plan-feature)<a href="https://agentmods.dev/commands/vishnu2kmohan/mcp-server-langgraph/plan-feature"><img src="https://agentmods.dev/badge/commands/vishnu2kmohan/mcp-server-langgraph/plan-feature.svg" alt="Measured on agentmods" 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 | $0.00017 | $0.01496 |
| Opus 5 | $0.00009 | $0.00748 |
| Sonnet 5 | $0.00003 | $0.00299 |
| Haiku 4.5 | $0.00002 | $0.00150 |
Grade A, and why
plan-feature 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 — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Feature Implementation
Create a detailed implementation plan for a new feature using deep thinking and structured task breakdown.
Usage
/plan-feature
This command uses "think harder" mode for comprehensive analysis.
Planning Framework
Phase 1: Requirements Analysis
Questions to Answer:
-
What needs to be built?
- Feature description
- Success criteria
- Acceptance criteria
-
Why is it needed?
- Business value
- User benefit
- Technical debt addressed
-
Who will use it?
- End users
- Internal systems
- APIs
-
When is it needed?
- Deadline
- Milestone
- Priority level
Phase 2: Technical Design
Architecture Considerations:
- Which modules will be affected?
- What new modules need to be created?
- How does it integrate with existing code?
- What design patterns apply?
- Are there relevant ADRs to follow?
Data Model:
- What data structures are needed?
- Database schema changes required?
- API request/response models?
- Validation rules?
Dependencies:
- External libraries needed?
- Internal module dependencies?
- Infrastructure requirements (Redis, PostgreSQL, etc.)?
- Configuration changes needed?
Phase 3: Task Breakdown
Create detailed TodoWrite task list with these categories:
Tests (TDD - Write First!):
- Unit tests for core logic
- Integration tests for APIs
- Edge case tests
- Error scenario tests
- Performance tests (if applicable)
Implementation:
- Data models (Pydantic classes)
- Business logic (core functions/classes)
- API endpoints (FastAPI routes)
- Middleware (if needed)
- Background tasks (if needed)
Integration:
- Database migrations (if schema changes)
- Configuration updates (env vars, config files)
- Dependency injection wiring
- OpenTelemetry instrumentation
- LangSmith tracing (if LLM-related)
Documentation:
- Docstrings for all public APIs
- CHANGELOG.md entry
- ADR (if architectural decision)
- README update (if user-facing)
- API documentation (OpenAPI)
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 · 238 lines · 17 tokens per session scan A 47684999b08d
plan-feature is a command published in the GitHub repository vishnu2kmohan/mcp-server-langgraph (4 stars, last pushed 10d ago), licensed MIT. It adds 17 tokens to every session and 1,496 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 2026-08-31.
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