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/ronmkr/promptbook/feature-devgit clone --depth 1 https://github.com/ronmkr/PromptBookWhat 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 | $0.00011 | $0.01063 |
| Opus 5 | $0.00005 | $0.00531 |
| Sonnet 5 | $0.00002 | $0.00213 |
| Haiku 4.5 | $0.00001 | $0.00106 |
Grade A, and why
feature-dev 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.
This is a copy
100% identical to feature-dev — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Development
You are helping a developer implement a new feature. Follow a systematic approach: understand the codebase deeply, identify and ask about all underspecified details, design elegant architectures, then implement.
Core Principles
- Ask clarifying questions: Identify all ambiguities, edge cases, and underspecified behaviors. Ask specific, concrete questions rather than making assumptions. Wait for user answers before proceeding with implementation. Ask questions early (after understanding the codebase, before designing architecture).
- Understand before acting: Read and comprehend existing code patterns first
- Read files identified by agents: When launching agents, ask them to return lists of the most important files to read. After agents complete, read those files to build detailed context before proceeding.
- Simple and elegant: Prioritize readable, maintainable, architecturally sound code
- Use TodoWrite: Track all progress throughout
Phase 1: Discovery
Goal: Understand what needs to be built
Initial request: $ARGUMENTS
Actions:
- Create todo list with all phases
- If feature unclear, ask user for:
- What problem are they solving?
- What should the feature do?
- Any constraints or requirements?
- Summarize understanding and confirm with user
Phase 2: Codebase Exploration
Goal: Understand relevant existing code and patterns at both high and low levels
Actions:
-
Launch 2-3 code-explorer agents in parallel. Each agent should:
- Trace through the code comprehensively and focus on getting a comprehensive understanding of abstractions, architecture and flow of control
- Target a different aspect of the codebase (eg. similar features, high level understanding, architectural understanding, user experience, etc)
- Include a list of 5-10 key files to read
Example agent prompts:
- "Find features similar to [feature] and trace through their implementation comprehensively"
- "Map the architecture and abstractions for [feature area], tracing through the code comprehensively"
- "Analyze the current implementation of [existing feature/area], tracing through the code comprehensively"
- "Identify UI patterns, testing approaches, or extension points relevant to [feature]"
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 · 126 lines · 11 tokens per session scan A 652e5d6264fd
feature-dev is a command published in the GitHub repository ronmkr/PromptBook (2 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 11 tokens to every session and 1,063 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to feature-dev, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
spec-design
Create comprehensive technical design for a specification.
execute
Executa o plano aprovado em .first-plan/07-state/plans/. Segue o plano à risca, para se algo invalidar premissa, gera relatório ao final.
pipeline-undo
Undo a pipeline run's result. With worktree isolation (the current engine), this is clean and low-risk: a run never touches your checkout — its result lives only on a pipeline/ branch (and, for a --push run, on the remote). "Undo" therefore means deleting that branch and its worktree, not reverting your working tree.
ox-session-pause
belongs in the ox CLI JSON output (guidance field), not here. Skills are agent-specific wrappers; ox serves all agents (Codex, etc.). --> Suspend the current session recording. Local cache continues to receive entries, but the upload at stop time will exclude the suspended range.
setup_research_plan
Set up or start a research project.
export
GDPR Article 20 — export all memories you own as portable JSON.