agent_spawn

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It discloses side effects (writes to blackboard), return format, and error conditions. However, it does not mention potential overwrites or authorization requirements, leaving minor gaps.

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?

Four sentences, each adding value: purpose, return values, error handling, usage advice. No fluff, front-loaded with the primary action.

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 5 parameters, 3 required, no output schema, and sibling tools, the description covers purpose, usage workflow, error cases, and return types. It is sufficiently complete for an AI agent to use correctly.

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?

Schema has 100% coverage, so baseline is 3. Description adds value by giving examples for agent_id and task_key, noting ttl default, and clarifying payload_json is optional. This enhances understanding beyond the 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?

Description clearly states the tool writes a task to the blackboard to dispatch work to an agent, with specific success/error return patterns. It distinguishes itself from siblings like blackboard_write and agent_list by focusing on task dispatch for agents.

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?

Explicitly advises to call agent_list first to confirm the agent exists and to verify with blackboard_read after spawning, providing a clear pre- and post-usage workflow. Also details error conditions for missing fields.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.