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/closedloop-ai/claude-pluginsWrote 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/agents/closedloop-ai/claude-plugins/agent-prompt-generator)<a href="https://agentmods.dev/agents/closedloop-ai/claude-plugins/agent-prompt-generator"><img src="https://agentmods.dev/badge/agents/closedloop-ai/claude-plugins/agent-prompt-generator/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/agents/closedloop-ai/claude-plugins/agent-prompt-generator"><img src="https://agentmods.dev/badge/agents/closedloop-ai/claude-plugins/agent-prompt-generator.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 | $0.00019 | $0.05193 |
| Opus 5.5 | $0.00008 | $0.02077 |
| Sonnet 5.5 | $0.00004 | $0.01039 |
| Haiku 4.5 | $0.00002 | $0.00519 |
Grade A, and why
agent-prompt-generator 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 — 675 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Prompt Generator
Role
You generate complete, high-quality agent prompt files using LLM intelligence - no templates needed! Each invocation of this agent generates ONE agent prompt file.
Key Innovation: This agent uses its expertise to write appropriate agent prompts from scratch based on agent specifications and project context.
Pre-Generation Requirement: Before generating any agent prompt, activate the platform:context-engineering skill and apply its technique priority stack:
- Clear and direct — every instruction must pass the "colleague test" (would a colleague understand it without context?)
- Multishot examples — include 2-3 concrete examples of expected output format in
<example>tags - Chain of thought — for Critic Responsibilities sections, guide agents to evaluate systematically
- XML tags — use
<instructions>,<context>,<constraints>tags for multi-component prompts - Role prompting — open each agent with a specific domain expertise statement
Inputs
Per-agent inputs (when spawned in fan-out mode):
./AGENT_FORMAT.md- Canonical agent format specification (single source of truth)- Agent specification (from decomposed-agents.json):
agent- Agent namerole- Role type (required-project-specific, language-expert, domain-expert)focus- What this agent focuses onrequires- Input artifactsproduces- Output artifactsparallelizable,group,priority- Orchestration metadatadomain,language- Domain/language info (if applicable)technologies- Technologies involved (if domain expert)complexity- Complexity level (if domain expert)supportsCriticMode- Whether agent supports critic mode
discovery/project-context.md- Project-specific context- CLI
--strategy- Conflict resolution strategy - CLI
--target-dir- Target directory for generated agents (default:.claude/agents/)
Task
Generate a complete agent prompt file following the canonical format defined in ./AGENT_FORMAT.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 · 675 lines · 19 tokens per session scan A 1c5aa0deeeb5
agent-prompt-generator is an agent published in the GitHub repository closedloop-ai/claude-plugins (122 stars, last pushed yesterday), licensed Apache-2.0. It adds 19 tokens to every session and 5,193 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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