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/smart-ai-memory/attune-ai/agentgit clone --depth 1 https://github.com/Smart-AI-Memory/attune-aiWrote 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/smart-ai-memory/attune-ai/agent)<a href="https://agentmods.dev/commands/smart-ai-memory/attune-ai/agent"><img src="https://agentmods.dev/badge/commands/smart-ai-memory/attune-ai/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 | $0.00008 | $0.00792 |
| Opus 5 | $0.00004 | $0.00396 |
| Sonnet 5 | $0.00002 | $0.00158 |
| Haiku 4.5 | $0.00001 | $0.00079 |
Grade A, and why
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 today.
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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
agent
Create and manage custom AI agents and multi-agent teams.
Quick Shortcuts
| Shortcut | Action |
|---|---|
/agent create <name> |
Create a new agent definition |
/agent list |
List all available agents |
/agent run <name> |
Execute an agent or agent team |
/agent release-prep |
Run the release readiness agent team |
Natural Language
Describe what you need:
- "create a code review agent"
- "what agents are available?"
- "run the release prep team"
- "I need a specialized agent for testing"
CRITICAL: Workflow Execution Instructions
When this command is invoked with arguments, you MUST execute the workflow, not answer ad-hoc.
Context Gathering (ALWAYS DO FIRST)
Before executing any action below, gather current project context:
- Run:
git status --short - Run:
git log --oneline -5 - Run:
git branch --show-current
Use this context to inform agent operations (e.g., current branch, recent changes).
Shortcut Routing (EXECUTE THESE)
| Input | Action |
|---|---|
/agent create <name> |
Guide through agent definition: role, tools, model tier, coordination pattern |
/agent list |
Scan src/attune/agents/ directory, list agents with descriptions and capabilities |
/agent run <name> |
Execute the named agent or agent team |
/agent release-prep |
Run release readiness agent team |
Natural Language Routing (EXECUTE THESE)
| Pattern | Action |
|---|---|
| "create", "new agent", "define" | Guide agent creation |
| "list", "available", "what agents" | List available agents |
| "run", "execute", "start" | Run specified agent |
| "release", "release-prep", "readiness" | Run release-prep agent team |
IMPORTANT: When arguments are provided, DO NOT just display documentation. EXECUTE the action.
Agent Definition Format
When creating agents, use this structure in src/attune/agents/<name>/:
<name>/
__init__.py # Agent exports
agent.py # Agent class definition
prompts.py # Agent-specific prompts
tools.py # Custom tools (optional)
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.
- today First seen · 107 lines · 8 tokens per session scan A 542595c97b9f
agent is a command published in the GitHub repository Smart-AI-Memory/attune-ai (10 stars, last pushed today), licensed Apache-2.0. It adds 8 tokens to every session and 792 once invoked, about $0.0000 per session on Opus 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 2026-09-03.
Other commands, from other repositories
agentos-status
Show AgentOS system status — agents, workers, health.
agentos-tui
Launch the AgentOS TUI dashboard.
council-sweep
Walk the configured watch paths and run Council on every artifact modified in the last N hours (default 24h).
council-review
Run the 5-agent Council on the current file or a specified path. Returns SHIP / REVISE / HOLD plus a revision brief.
agentos-chat
Send a message to an AgentOS agent.
agentos-evolve
Quick evolve a function — generate, register, and evaluate.