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agent_spawn

Write a task to a blackboard to assign it to a specific agent, who will execute it on its next poll cycle.

Instructions

Write a task record to the blackboard to dispatch work to a named agent on its next poll cycle. Returns {ok:true, taskKey, agentId, instruction, written:true} on success. Returns {ok:false, error:"..."} if agent_id, task_key, or instruction is missing, or if payload_json is malformed. Call agent_list first to confirm the target agent is registered; verify the task was recorded with blackboard_read after spawning.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesID of the agent to assign the task to (e.g. "code_writer", "data_analyst")
task_keyYesBlackboard key for the task (e.g. "task:write:auth_module")
instructionYesNatural language instruction for the agent
payload_jsonNoOptional JSON-encoded extra payload for the agent
ttlNoTime-to-live for the task entry in seconds (default: 3600)
Behavior4/5

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

Without annotations, the description carries full burden. It discloses return formats for success and error, lists specific error conditions, and implies async dispatch (on next poll cycle). Lacks details on idempotency or overwrite behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three well-structured sentences with no wasted words. Each sentence serves a distinct purpose: purpose, behavior, usage guidance. Front-loaded with core functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description thoroughly explains return values and error cases. It covers prerequisites, verification steps, and all parameters. Sufficient for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers 100% of parameters with descriptions. The description adds value by stating the default TTL (3600) and explaining the output structure, which is not in the schema. Good enhancement.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool dispatches work to a named agent by writing a task record to the blackboard. It uses specific verbs (write, dispatch) and resources (task record, named agent), distinguishing it from siblings like blackboard_write.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description advises to call agent_list first to confirm registration and to verify with blackboard_read after spawning. It also lists error conditions. However, it does not explicitly state when not to use this tool versus alternatives like blackboard_write.

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

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