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.
git clone --depth 1 https://github.com/wmeints/context-engineeringWrote 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/wmeints/context-engineering/generate-plan)<a href="https://agentmods.dev/commands/wmeints/context-engineering/generate-plan"><img src="https://agentmods.dev/badge/commands/wmeints/context-engineering/generate-plan/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/wmeints/context-engineering/generate-plan"><img src="https://agentmods.dev/badge/commands/wmeints/context-engineering/generate-plan.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00000 | $0.00486 |
| Opus 5.5 | $0.00000 | $0.00194 |
| Sonnet 5.5 | $0.00000 | $0.00097 |
| Haiku 4.5 | $0.00000 | $0.00049 |
Grade A, and why
generate-plan 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 1mo 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create requirements document
Feature: $ARGUMENTS
Generate a complete requirements document for feature implementation based on thorough research. Ensure context is passed to the agent to enable self-validation and iterative improvements. Read the requirements file first to understand what needs to be done, how examples provided help, and any other considerations.
The agent only gets access to the context you're appending to the requirements document. Assume that the agent has access to the code base and the same knowledge cut-off as you, so it's important that your research is included or referenced in the requirements document. The agent has websearch capabilities, so pass URLs to documentation and examples.
Research process
- Codebase analysis
- Search for similar patterns/features in the code base
- Identify files to reference in the requirements document
- Note existing conventions to follow
- Check test patterns for validation
- External research
- Search for similar features/patterns online
- Library documentation (include specific URLs)
- Implementation examples (Github/blogs)
- Best practices and common pitfalls
- User clarification
- Specific patterns to mirror and where to find them
- Integration requirements and where to find them
Requirements document generation
Critical context to pass
- Documentation: URLs to specific sections
- Code Examples: Real snippets from the code base
- Gotchas: Library quirks, version issues
- Patterns: Existing approaches to follow
Implementation blueprint
- Start with pseudocode showing the approach
- Reference real files for patterns
- Include error handling strategies
- List tasks to be completed to fulfill the requirements in order of completion
Validation gates
dotnet test
It's important to verify the requirements and plan your approach before writing the requirements document.
Output
Save the requirements as docs/implementation-plans/{feature-name}.md
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.
- 1mo ago First seen · 79 lines · 0 tokens per session scan A b95dd2d77e5b
generate-plan is a command published in the GitHub repository wmeints/context-engineering (37 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 486 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.
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