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/bravew/trove/prp-creategit clone --depth 1 https://github.com/bravew/troveWhat 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 | $0.00010 | $0.01194 |
| Opus 5 | $0.00005 | $0.00597 |
| Sonnet 5 | $0.00002 | $0.00239 |
| Haiku 4.5 | $0.00001 | $0.00119 |
Grade A, and why
prp-create 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 — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Feature PRP
Feature: $ARGUMENTS
Mission
Transform a feature request into a comprehensive implementation PRP (Pull Request Plan) through systematic codebase analysis, external research, and strategic planning.
Core Principle: We do NOT write code in this phase. Our goal is to create a battle-tested, context-rich implementation plan that enables one-pass implementation success.
Key Philosophy: Context is King. The PRP must contain ALL information needed for implementation — patterns, gotchas, documentation, validation commands — so the execution agent succeeds on the first attempt.
Planning Process
Phase 1: Feature Understanding
- Extract the core problem being solved
- Identify user value and business impact
- Determine feature type: New Capability / Enhancement / Refactor / Bug Fix
- Assess complexity: Low / Medium / High
- Map affected systems and components
Phase 2: Codebase Intelligence Gathering
Use specialized agents and parallel analysis:
1. Project Structure Analysis
- Check CLAUDE.md / project rules for conventions
- Read config files (package.json, pyproject.toml, Package.swift, etc.)
- Map directory structure, module organization, and routing patterns
- Identify the project's validation commands (lint, type-check, test, build)
2. Pattern Recognition (use subagents when beneficial)
- Search for similar implementations in the codebase
- Identify coding conventions (naming, structure, error handling, testing)
- Extract common patterns for the feature's domain
- Document anti-patterns to avoid
3. Dependency Analysis
- Catalog external libraries relevant to the feature
- Understand how libraries are integrated
- Note library versions and compatibility requirements
4. Testing Patterns
- Identify the project's test framework and structure
- Find similar test examples for reference
- Note validation commands
5. Integration Points
- Identify existing files that need updates
- Determine new files that need creation and their locations
- Map routing, state management, and API patterns if applicable
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 · 201 lines · 10 tokens per session scan A 4aa2c12de1ec
prp-create is a command published in the GitHub repository bravew/trove (10 stars, last pushed 3d ago), licensed MIT. It adds 10 tokens to every session and 1,194 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.
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.