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 agents/a5c-ai/babysitter/droidgit clone --depth 1 https://github.com/a5c-ai/babysitterWrote 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/a5c-ai/babysitter/droid)<a href="https://agentmods.dev/agents/a5c-ai/babysitter/droid"><img src="https://agentmods.dev/badge/agents/a5c-ai/babysitter/droid.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 | $0.00000 | $0.01600 |
| Opus 5 | $0.00000 | $0.00800 |
| Sonnet 5 | $0.00000 | $0.00320 |
| Haiku 4.5 | $0.00000 | $0.00160 |
Grade C, and why
droid scanned grade C with 2 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 3d 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -fsSL https://get.factory.ai/droid | bash Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
### curl (Universal) How it starts
The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Droid
Factory AI's enterprise-grade AI coding agent with terminal integration and sophisticated workflow automation.
Overview
Factory Droid is a top-performing AI coding agent built by Factory AI that provides end-to-end development workflows, debugging, refactoring, and CI/CD integration. Droid scores 58.75% on terminal benchmarks and supports both interactive chat and headless automation modes.
Installation
NPM (Recommended)
npm install -g @factory/cli
Homebrew (macOS)
brew install factory/tap/droid
curl (Universal)
curl -fsSL https://get.factory.ai/droid | bash
Authentication
Factory AI Account Setup
- Sign up at factory.ai/signup
- Install Droid CLI (see Installation above)
- Authenticate with Factory AI:
droid auth login - Verify authentication:
droid whoami
Environment Variables
export DROID_API_KEY=your_factory_api_key
Usage with adapters
Basic Chat
adapters run droid --prompt "Help me refactor this API endpoint"
Resume Session
adapters run droid --session-id abc123 --prompt "Continue with the optimization"
Model Selection
adapters run droid --model gpt-5-turbo --prompt "Generate a complete REST API"
adapters run droid --model claude-sonnet --prompt "Review this code for security issues"
adapters run droid --model gemini-flash --prompt "Create unit tests for this module"
Auto-approve Tools (Yolo Mode)
adapters run droid --tool-approval-mode yolo --prompt "Fix all linting errors in src/"
Working Directory
adapters run droid --cwd /path/to/project --prompt "Analyze the codebase structure"
Supported Models
| Model ID | Alias | Context Window | Output Tokens | Input Price | Output Price |
|---|---|---|---|---|---|
gpt-5-turbo |
gpt-5-turbo |
256,000 | 16,384 | $2.00/1M | $8.00/1M |
claude-3-5-sonnet-20241022 |
claude-sonnet |
200,000 | 8,192 | $3.00/1M | $15.00/1M |
gemini-2-flash |
gemini-flash |
1,000,000 | 8,192 | $0.075/1M | $0.30/1M |
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.
- 3d ago First seen · 257 lines · 0 tokens per session scan C 069af4d5f17e
droid is an agent published in the GitHub repository a5c-ai/babysitter (1,762 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,600 tokens. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
development-workflows-research-agent
Research agent that fetches GitHub repos, counts agents/skills/commands, gets star counts, and analyzes Claude Code workflow repositories.
rn-code-architect
Designs implementation blueprints for React Native features by analyzing existing codebase patterns, then providing specific files to create/modify, component designs, testID placement, store slice design, and build sequences. Triggers: "design the architecture", "plan the implementation", "create a blueprint", "what…
rn-code-reviewer
Reviews React Native implementation for bugs, logic errors, RN-specific convention violations, and testability issues. Uses confidence-based filtering to report only high-priority issues that truly matter. Triggers: "review this code", "check for bugs", "review the implementation", "are there any issues", "check…
design-author
Use after research is complete to draft the approach before any code is written. Drafts a 200-line design document covering current state, desired end state, patterns to follow, and decisions made. Resolves its own open questions autonomously, recording each as an explicit, auditable assumption in the design.
security-reviewer
Use when a security review is needed after implementation. Applies OWASP-style checks with fresh context. Critical findings are a hard gate — they block shipping until resolved. Example triggers — "security review", "check for vulnerabilities", "audit this code for security issues".
planner
Use after the structure is produced to create the tactical implementation plan. Translates each vertical slice in structure.md into precise file-level steps with acceptance test mappings. The plan is a tactical artifact for the implementer — neither the structure nor the plan is human-reviewed (the design passed…