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/coleam00/context-engineering-intro/execute-prpgit clone --depth 1 https://github.com/coleam00/context-engineering-introWhat 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 | $0.00291 |
| Opus 5 | $0.00000 | $0.00146 |
| Sonnet 5 | $0.00000 | $0.00058 |
| Haiku 4.5 | $0.00000 | $0.00029 |
Grade A, and why
execute-prp 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.
Copies of this mod
5 near-identical copies found in the catalogue:
- execute-prp — 100% identical, 1 lines differ
- execute-prp — 100% identical, 0 lines differ
- execute-prp — 100% identical, 0 lines differ
- execute-prp — 100% identical, 0 lines differ
- execute-prp — 100% identical, 0 lines differ
What it actually says
Execute BASE PRP
Implement a feature using using the PRP file.
PRP File: $ARGUMENTS
Execution Process
-
Load PRP
- Read the specified PRP file
- Understand all context and requirements
- Follow all instructions in the PRP and extend the research if needed
- Ensure you have all needed context to implement the PRP fully
- Do more web searches and codebase exploration as needed
-
ULTRATHINK
- Think hard before you execute the plan. Create a comprehensive plan addressing all requirements.
- Break down complex tasks into smaller, manageable steps using your todos tools.
- Use the TodoWrite tool to create and track your implementation plan.
- Identify implementation patterns from existing code to follow.
-
Execute the plan
- Execute the PRP
- Implement all the code
-
Validate
- Run each validation command
- Fix any failures
- Re-run until all pass
-
Complete
- Ensure all checklist items done
- Run final validation suite
- Report completion status
- Read the PRP again to ensure you have implemented everything
-
Reference the PRP
- You can always reference the PRP again if needed
Note: If validation fails, use error patterns in PRP to fix and retry.
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 · 40 lines · 0 tokens per session scan A 3a74ea61c0d6
execute-prp is a command published in the GitHub repository coleam00/context-engineering-intro (13,819 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 291 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.