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 skills/ronmkr/promptbook/agent-developmentnpx skills add ronmkr/PromptBook --skill agent-developmentgit clone --depth 1 https://github.com/ronmkr/PromptBookWrote 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/skills/ronmkr/promptbook/agent-development)<a href="https://agentmods.dev/skills/ronmkr/promptbook/agent-development"><img src="https://agentmods.dev/badge/skills/ronmkr/promptbook/agent-development.svg" alt="Measured on agentmods" 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 | $0.00081 | $0.02661 |
| Opus 5 | $0.00041 | $0.01331 |
| Sonnet 5 | $0.00016 | $0.00532 |
| Haiku 4.5 | $0.00008 | $0.00266 |
Grade A, and why
agent-development 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 4d 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
97% identical to agent-development — 18 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 — 402 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Development for Antigravity Plugins
Overview
Agents are autonomous subprocesses that handle complex, multi-step tasks independently. Understanding agent structure, triggering conditions, and system prompt design enables creating powerful autonomous capabilities.
Key concepts:
- Agents are FOR autonomous work, commands are FOR user-initiated actions
- Markdown file format with YAML frontmatter
- Triggering via description field with examples
- System prompt defines agent behavior
- Model and color customization
Agent File Structure
Complete Format
---
name: agent-identifier
description: Use this agent when [triggering conditions]. Typical triggers include [scenario 1 in prose], [scenario 2 in prose], and [scenario 3 in prose]. See "When to invoke" in the agent body for worked scenarios.
model: inherit
color: blue
tools: ["Read", "Write", "Grep"]
---
You are [agent role description]...
## When to invoke
[Two to four representative scenarios written as prose, e.g.:]
- **[Scenario name].** [What the situation looks like and what the agent should do.]
- **[Scenario name].** [Same.]
**Your Core Responsibilities:**
1. [Responsibility 1]
2. [Responsibility 2]
**Analysis Process:**
[Step-by-step workflow]
**Output Format:**
[What to return]
Frontmatter Fields
name (required)
Agent identifier used for namespacing and invocation.
Format: lowercase, numbers, hyphens only Length: 3-50 characters Pattern: Must start and end with alphanumeric
Good examples:
code-reviewertest-generatorapi-docs-writersecurity-analyzer
Bad examples:
helper(too generic)-agent-(starts/ends with hyphen)my_agent(underscores not allowed)ag(too short, < 3 chars)
description (required)
Defines when Gemini should trigger this agent. This is the most critical field — it is loaded into context whenever the agent is registered, so the harness can decide when to dispatch.
Must include:
- Triggering conditions ("Use this agent when...")
- A short prose summary of the typical trigger scenarios
- A pointer to a "When to invoke" section in the agent body for the detailed worked scenarios
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 402 lines · 81 tokens per session scan A 2bbd603715f1
agent-development is a skill published in the GitHub repository ronmkr/PromptBook (2 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 81 tokens to every session and 2,661 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to agent-development, differing in 18 lines, and is treated as a copy.
Other skills, from other repositories
testing
Testing workflow and quality standards for writing and running tests. Use when: (1) Writing new tests, (2) Adding a new feature that needs tests, (3) Modifying logic that has existing tests, (4) Before claiming a task is complete.
bug-audit
Weekly multi-agent audit for serious bugs (data integrity, silent caps, staleness, timestamp math, trust boundaries). Fans out Sonnet scanners + Opus deep auditors, adversarially verifies every finding, files GitHub issues for confirmed critical/high bugs. Trigger: /bug-audit.
multi-llm-review
Run complete, evidence-backed code reviews through the local stdio gateway across the seven canonical CLI providers: Claude, Codex, Gemini, Grok, Mistral, Devin, and Cursor. Use for quality, security, correctness, or release validation that requires independent reviewers.
retrospective-walk
Walk a human or agent through a diff, worktree, commit range, gateway job, or episode reference as a structured retrospective. Use after implement-review-fix or multi-LLM review cycles, when reviewing prior jobs or uncommitted work, or when durable evidence is needed for what changed, why it changed, who/when…
secure-orchestration
Orchestrate security-sensitive LLM work with the gateway's Claude-managed approval boundary, provider-native legacy controls, evidence-aware auditing, and complete no-limit review handling.
session-workflow
Manage gateway bookkeeping and provider-native conversation continuity across Claude, Codex, Gemini, Grok, Mistral, Devin, and Cursor. Use for multi-turn work, session inspection, and safe resume decisions.