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/julianromli/droid-factory-templateWrote 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/commands/julianromli/droid-factory-template/generate-agents)<a href="https://agentmods.dev/commands/julianromli/droid-factory-template/generate-agents"><img src="https://agentmods.dev/badge/commands/julianromli/droid-factory-template/generate-agents/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/commands/julianromli/droid-factory-template/generate-agents"><img src="https://agentmods.dev/badge/commands/julianromli/droid-factory-template/generate-agents.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 | $0.00010 | $0.02063 |
| Opus 5.5 | $0.00004 | $0.00825 |
| Sonnet 5.5 | $0.00002 | $0.00413 |
| Haiku 4.5 | $0.00001 | $0.00206 |
Grade A, and why
generate-agents 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 2mo 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 — 248 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Task: Analyze this codebase and generate a hierarchical AGENTS.md structure
Context & Principles
You are going to help me create a hierarchical AGENTS.md system for this codebase. This is critical for AI coding agents to work efficiently with minimal token usage.
Core Principles:
- Root AGENTS.md is LIGHTWEIGHT - Only universal guidance, links to sub-files
- Nearest-wins hierarchy - Agents read the closest AGENTS.md to the file being edited
- JIT (Just-In-Time) indexing - Provide paths/globs/commands, NOT full content
- Token efficiency - Small, actionable guidance over encyclopedic documentation
- Sub-folder AGENTS.md files have MORE detail - Specific patterns, examples, commands
Your Process
Phase 1: Repository Analysis
First, analyze the codebase structure and provide me with:
-
Repository type: Monorepo, multi-package, or simple single project?
-
Primary technology stack: Languages, frameworks, key tools
-
Major directories/packages that should have their own AGENTS.md:
- Apps (e.g.,
apps/web,apps/api,apps/mobile) - Services (e.g.,
services/auth,services/transcribe) - Packages/libs (e.g.,
packages/ui,packages/shared) - Workers/jobs (e.g.,
workers/queue,workers/cron)
- Apps (e.g.,
-
Build system: pnpm/npm/yarn workspaces? Turborepo? Lerna? Or simple?
-
Testing setup: Jest, Vitest, Playwright, pytest? Where are tests?
-
Key patterns to document:
- Code organization patterns
- Important conventions (naming, styling, commits)
- Critical files that serve as good examples
- Anti-patterns to avoid
Present this as a structured map before generating any AGENTS.md files.
Phase 2: Generate Root AGENTS.md
Create a lightweight root AGENTS.md (~100-200 lines max) that includes:
Required Sections:
1. Project Snapshot (3-5 lines)
- Repo type (monorepo/simple)
- Primary tech stack
- Note that sub-packages have their own AGENTS.md files
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.
- 2mo ago First seen · 248 lines · 10 tokens per session scan A d6254fb4870b
generate-agents is a command published in the GitHub repository julianromli/droid-factory-template (53 stars, last pushed 10mo ago), licensed MIT. It adds 10 tokens to every session and 2,063 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 commands, from other repositories
checklist
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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.
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.