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/jwynia/context-networks/plangit clone --depth 1 https://github.com/jwynia/context-networksWhat 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 | $0.00000 | $0.01916 |
| Opus 5 | $0.00000 | $0.00958 |
| Sonnet 5 | $0.00000 | $0.00383 |
| Haiku 4.5 | $0.00000 | $0.00192 |
Grade A, and why
plan scanned grade A with 0 findings against 26 rules in 11 categories โ prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency โ 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 โ 307 lines โ stays where its author put it; the contents beside it link to each section on GitHub.
Planning & Architecture Mode
๐ซ Implementation Restrictions
THIS IS A PLANNING-ONLY COMMAND
You are now in Planning & Architecture Mode for: $ARGUMENTS
In this mode, you MUST:
- โ Research and understand the problem space
- โ Document findings in the context network
- โ Design architecture and patterns
- โ Create task breakdowns
- โ Identify dependencies and risks
You MUST NOT:
- โ Write implementation code
- โ Create files outside context-network/
- โ Modify existing code
- โ Run build or deployment commands
- โ Make configuration changes
Planning Process
Phase 1: Problem Understanding ๐
-
Define the Problem
- What are we trying to solve?
- Why does this matter?
- Who are the stakeholders?
- What are the success criteria?
-
Explore the Current State
- Search existing codebase for related functionality
- Check context network for prior decisions
- Identify what already exists
- Document current limitations
-
Gather Requirements
- Functional requirements
- Non-functional requirements (performance, security, etc.)
- Constraints and boundaries
- Assumptions to validate
Phase 2: Research & Discovery ๐ฌ
-
Research Existing Solutions
- Industry patterns and best practices
- Similar implementations in the codebase
- External libraries or frameworks
- Academic or theoretical foundations
-
Technology Evaluation
- Available tools and technologies
- Compatibility with existing stack
- Learning curve and team expertise
- Long-term maintenance implications
-
Document Findings
context-network/research/$ARGUMENTS/ โโโ overview.md # Problem and research summary โโโ findings.md # Detailed discoveries โโโ alternatives.md # Options considered โโโ recommendations.md # Suggested approach
Phase 3: Architecture Design ๐
- High-Level Design
- System boundaries and interfaces
- Component relationships
- Data flow diagrams
- Sequence diagrams for key scenarios
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 ยท 307 lines ยท 0 tokens per session scan A 0e2ac263b12f
plan is a command published in the GitHub repository jwynia/context-networks (24 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,916 tokens. 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.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.