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 commands/frankxai/agentic-creator-os/auto-agentgit clone --depth 1 https://github.com/frankxai/agentic-creator-osWrote 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/frankxai/agentic-creator-os/auto-agent)<a href="https://agentmods.dev/commands/frankxai/agentic-creator-os/auto-agent"><img src="https://agentmods.dev/badge/commands/frankxai/agentic-creator-os/auto-agent.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 5.1 | $0.00000 | $0.00621 |
| Opus 5 | $0.00000 | $0.00311 |
| Sonnet 5 | $0.00000 | $0.00124 |
| Haiku 4.5 | $0.00000 | $0.00062 |
Grade A, and why
auto-agent 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 yesterday.
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
100% identical to auto-agent — 0 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
auto agent
Automatically spawn and manage agents based on task requirements.
Usage
npx claude-flow auto agent [options]
Options
--task, -t <description>- Task description for agent analysis--max-agents, -m <number>- Maximum agents to spawn (default: auto)--min-agents <number>- Minimum agents required (default: 1)--strategy, -s <type>- Selection strategy: optimal, minimal, balanced--no-spawn- Analyze only, don't spawn agents
Examples
Basic auto-spawning
npx claude-flow auto agent --task "Build a REST API with authentication"
Constrained spawning
npx claude-flow auto agent -t "Debug performance issue" --max-agents 3
Analysis only
npx claude-flow auto agent -t "Refactor codebase" --no-spawn
Minimal strategy
npx claude-flow auto agent -t "Fix bug in login" -s minimal
How It Works
-
Task Analysis
- Parses task description
- Identifies required skills
- Estimates complexity
- Determines parallelization opportunities
-
Agent Selection
- Matches skills to agent types
- Considers task dependencies
- Optimizes for efficiency
- Respects constraints
-
Topology Selection
- Chooses optimal swarm structure
- Configures communication patterns
- Sets up coordination rules
- Enables monitoring
-
Automatic Spawning
- Creates selected agents
- Assigns specific roles
- Distributes subtasks
- Initiates coordination
Agent Types Selected
- Architect: System design, architecture decisions
- Coder: Implementation, code generation
- Tester: Test creation, quality assurance
- Analyst: Performance, optimization
- Researcher: Documentation, best practices
- Coordinator: Task management, progress tracking
Strategies
Optimal
- Maximum efficiency
- May spawn more agents
- Best for complex tasks
- Highest resource usage
Minimal
- Minimum viable agents
- Conservative approach
- Good for simple tasks
- Lowest resource usage
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.
- yesterday First seen · 123 lines · 0 tokens per session scan A 40f23f854dc0
auto-agent is a command published in the GitHub repository frankxai/agentic-creator-os (10 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 621 tokens. A static security scan graded it A with 0 findings. It is 100% identical to auto-agent, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
meeting-notes
Summarize a meeting transcript into structured notes with decisions, action items, and follow-ups.
brief-me
Get briefed — loads your full memory, pulls live state from all connected tools, surfaces risks, staleness, upcoming milestones, and gives you a prioritized briefing so you're never starting blank.
write-stories
Break a feature into backlog items — user stories, job stories, or WWA format with acceptance criteria.
develop
Implement skill development issues with TDD-governed workflow.
welcome
60-second orientation for newcomers. Shows the two tracks (builder / creator), the four routes, the delivery menu, and where to go next. No commitment extracted — that's /intake's job.
handoff
Generate a copy-pasteable resume prompt for a fresh Claude Code session.