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/smart-ai-memory/attune-ai/referencegit clone --depth 1 https://github.com/Smart-AI-Memory/attune-aiWhat 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 | $0.00002 | $0.00983 |
| Opus 5 | $0.00001 | $0.00491 |
| Sonnet 5 | $0.00000 | $0.00197 |
| Haiku 4.5 | $0.00000 | $0.00098 |
Grade A, and why
agents-reference 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 2d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Universal Agent Factory — create, run, and orchestrate AI agents across frameworks
Reference
The public surface is re-exported from attune.agent_factory:
AgentFactory, Framework, BaseAdapter, BaseAgent, AgentConfig,
WorkflowConfig, AgentRole, AgentCapability.
AgentFactory — attune.agent_factory
| Member | Purpose |
|---|---|
AgentFactory(framework=None, provider="anthropic", api_key=None, use_case="general") |
Construct the factory; framework defaults to native. |
create_agent(name, role=AgentRole.CUSTOM, model_tier="capable", ...) -> BaseAgent |
Build an agent. |
create_workflow(name, agents, mode="sequential", ...) -> BaseWorkflow |
Build a coordinating workflow. |
create_tool(name, description, func, args_schema=None) |
Wrap a callable as a tool. |
create_coordinator / create_researcher / create_writer / create_reviewer / create_debugger(...) -> BaseAgent |
Role-preset agents. |
create_code_review_pipeline() -> BaseWorkflow · create_research_pipeline(topic="", include_reviewer=True) -> BaseWorkflow |
Ready-made pipelines. |
get_agent(name) -> BaseAgent | None · list_agents() -> list[str] |
Look up created agents. |
list_frameworks(installed_only=True) -> list[dict] · recommend_framework(use_case="general") -> Framework · switch_framework(framework) -> None |
Framework management. |
BaseAgent / BaseWorkflow
BaseAgent is re-exported from attune.agent_factory; BaseWorkflow
lives in attune.agent_factory.base. You rarely import either directly
— the factory's create_agent / create_workflow return them.
| Member | Purpose |
|---|---|
BaseAgent.invoke(input_data, context=None) -> dict |
Async. Run the agent once. |
BaseAgent.stream(input_data, context=None) |
Async generator of incremental output. |
BaseAgent.add_tool(tool) · get_conversation_history() · clear_history() |
Tool + history management. |
BaseWorkflow.run(input_data, initial_state=None) -> dict |
Async. Run the multi-agent workflow. |
BaseWorkflow.stream(input_data, initial_state=None) |
Async generator. |
BaseWorkflow.get_agent(name) · get_state() |
Inspect the workflow. |
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.
- 2d ago First seen · 72 lines · 2 tokens per session scan A 90f562503023
agents-reference is an agent published in the GitHub repository Smart-AI-Memory/attune-ai (10 stars, last pushed 2d ago), licensed Apache-2.0. It adds 2 tokens to every session and 983 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 2026-08-31.
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