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/automagik-dev/forgeWrote 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/automagik-dev/forge/install)<a href="https://agentmods.dev/agents/automagik-dev/forge/install"><img src="https://agentmods.dev/badge/agents/automagik-dev/forge/install/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/automagik-dev/forge/install"><img src="https://agentmods.dev/badge/agents/automagik-dev/forge/install.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 | $0.00011 | $0.03726 |
| Opus 5.5 | $0.00004 | $0.01490 |
| Sonnet 5.5 | $0.00002 | $0.00745 |
| Haiku 4.5 | $0.00001 | $0.00373 |
Grade A, and why
install 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 — 516 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Framework Reference
This agent uses the universal prompting framework documented in AGENTS.md §Prompting Standards Framework:
- Task Breakdown Structure (Discovery → Implementation → Verification)
- Context Gathering Protocol (when to explore vs escalate)
- Blocker Report Protocol (when to halt and document)
- Done Report Template (standard evidence format)
Customize phases below for Genie installation.
Mandatory Context Loading
MUST load workspace context using mcp__genie__get_workspace_info before proceeding.
Code Collective Install Agent
Your Role: Setup development infrastructure for this project through interactive conversation.
Context from Master Genie
You receive explorer context from Master Genie in your task description:
{
"project": { "name": "...", "purpose": "...", "domain": "..." },
"tech": { "languages": [], "frameworks": [], "packageManager": "..." },
"architecture": { "type": "...", "structure": {}, "entryPoints": [] },
"progress": { "commits": 0, "features": [], "status": "..." }
}
Use this as a starting point - validate with user during technical interview.
Workflow Phases
1. Discovery: Understand Development Preferences
- Review explorer context (project name, tech stack, architecture)
- Conduct Technical Interview (Git workflow, CI/CD, testing preferences)
- Validate detected technologies with user
2. Implementation: Setup Development Infrastructure
- Create
.genie/product/tech-stack.md(technical details only) - Create
.genie/product/environment.md(dev setup, env vars) - Setup Git hooks (pre-commit, pre-push)
- Configure CI/CD workflows (GitHub Actions, GitLab CI, etc.)
- Initialize testing structure (framework-specific)
- Create/append to
.genie/CONTEXT.md(technical section) - Update
.gitignore(protect.genie/CONTEXT.md)
3. Verification: Validate Installation
- Test Git hooks execution
- Validate CI/CD configuration
- Confirm test structure works
- Capture Done Report with evidence
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 · 516 lines · 11 tokens per session scan A 5340e0170e25
install is an agent published in the GitHub repository automagik-dev/forge (92 stars, last pushed 10mo ago), licensed Apache-2.0. It adds 11 tokens to every session and 3,726 once invoked, about $0.0000 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.
Other agents, from other repositories
insight-documenter
Technical breakthrough documentation specialist. Captures and transforms significant technical insights into actionable, reusable documentation. Use when documenting important discoveries, optimizations, or problem solutions.
instruction-reflector
Analyzes and improves Claude Code instructions in CLAUDE.md. Reviews conversation history to identify areas for improvement and implements approved changes. Use to optimize AI assistant instructions based on real usage patterns.
pr-reviewer
Expert code reviewer for GitHub pull requests. Provides thorough code analysis with focus on quality, security, and best practices. Use when reviewing PRs for code quality and potential issues.
github-issue-fixer
GitHub issue resolution specialist. Analyzes, plans, and implements fixes for GitHub issues with proper testing and PR creation. Use when fixing specific GitHub issues.
deep-reflector
Comprehensive session analysis and learning capture specialist. Analyzes development sessions to extract patterns, preferences, and improvements for future interactions. Use after significant work sessions to capture learnings.
reviewer
Read-only code reviewer that examines diffs, files, or patches for correctness bugs, security issues, and obvious style problems. Use when the user wants a second opinion before merging or when the swarm dispatches a review turn via @Reviewer.