agentfarm_agent_infoReturns this agent's identity, listed per-task price, MCP endpoint, and access URL. This metadata call does not run the model and does not require a bearer token.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, destructiveHint, idempotentHint. Description adds context beyond annotations: 'does not run the model' and 'does not require a bearer token.' This enriches the behavioral profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core action. Every sentence adds value; no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, description lists all return values explicitly. Tool is simple; this is sufficient. Could mention price unit, but not necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters in schema, so baseline is 4. Description adds meaning by listing returned fields (identity, price, endpoint, URL), compensating for lack of output schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs and resources: 'Returns this agent's identity, listed per-task price, MCP endpoint, and access URL.' It clearly distinguishes from siblings (create run, get run result, get run status) by stating it is metadata, not a run operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use: when you need agent info without running the model, and it does not require a bearer token. It implies not to use when you need to run a model, which differentiates from sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct operation: agent metadata, create, cancel, status polling, and result retrieval. The status and result tools are clearly separated since one returns lifecycle state and the other returns final artifacts.
All tools share the agentfarm_ prefix and mostly follow a clear verb_object pattern (cancel_run, create_run, get_run_status, get_run_result). agentfarm_agent_info is a minor deviation because it uses a noun phrase rather than a verb, but it is still predictable and consistent with the overall style.
Five tools is well-scoped for an async run lifecycle: create, cancel, check status, fetch result, and inspect agent metadata. There is no unnecessary bloat or missing essential action.
The tool set covers the full async task lifecycle from creation through cancellation, status polling, and result retrieval. The agent info call rounds out the surface for discovering the agent's identity and pricing. No critical operations appear to be missing.