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twining_delegate

Delegate tasks to agents by posting capability requirements to a shared blackboard and receive ranked suggestions based on match quality.

Instructions

Post a delegation request to the blackboard as a 'need' entry with capability requirements. Returns suggested agents ranked by match quality.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
summaryYesDescription of the task to delegate (max 200 chars)
required_capabilitiesYesCapabilities needed for this task
urgencyNoUrgency level affecting timeout (default: 'normal')
timeout_msNoCustom timeout in ms (overrides urgency-based default)
scopeNoScope for the delegation (default: 'project')
tagsNoAdditional tags for the delegation entry
agent_idNoID of the delegating agent (default: 'main')

Implementation Reference

  • The implementation of the 'twining_delegate' tool in `src/tools/coordination-tools.ts`. It registers the tool with the MCP server and delegates the execution to `coordinationEngine.postDelegation`.
    // twining_delegate — Post a delegation request to the blackboard
    server.registerTool(
      "twining_delegate",
      {
        description:
          "Post a delegation request to the blackboard as a 'need' entry with capability requirements. Returns suggested agents ranked by match quality.",
        inputSchema: {
          summary: z
            .string()
            .describe("Description of the task to delegate (max 200 chars)"),
          required_capabilities: z
            .array(z.string())
            .describe("Capabilities needed for this task"),
          urgency: z
            .enum(["high", "normal", "low"])
            .optional()
            .describe("Urgency level affecting timeout (default: 'normal')"),
          timeout_ms: z
            .number()
            .optional()
            .describe("Custom timeout in ms (overrides urgency-based default)"),
          scope: z
            .string()
            .optional()
            .describe("Scope for the delegation (default: 'project')"),
          tags: z
            .array(z.string())
            .optional()
            .describe("Additional tags for the delegation entry"),
          agent_id: z
            .string()
            .optional()
            .describe("ID of the delegating agent (default: 'main')"),
        },
      },
      async (args) => {
        try {
          const result = await coordinationEngine.postDelegation({
            summary: args.summary,
            required_capabilities: args.required_capabilities,
            urgency: args.urgency,
            timeout_ms: args.timeout_ms,
            scope: args.scope,
            tags: args.tags,
            agent_id: args.agent_id,
          });
          return toolResult(result);
        } catch (e) {
          return toolError(
            e instanceof Error ? e.message : "Unknown error",
            "INTERNAL_ERROR",
          );
        }
      },
    );
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool posts a request and returns ranked suggestions, but lacks details on permissions, side effects, rate limits, or error handling. This is inadequate for a tool that likely involves system-wide coordination.

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?

The description is a single, efficient sentence that front-loads the core action and outcome with zero waste. Every word contributes to understanding the tool's function.

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

Completeness2/5

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

For a complex delegation tool with 7 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, usage context, and return value specifics beyond 'ranked by match quality', leaving significant gaps for an AI agent to operate effectively.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema fully documents all 7 parameters. The description adds no additional parameter semantics beyond what the schema provides, such as explaining how 'required_capabilities' are matched or how 'urgency' affects ranking. Baseline 3 is appropriate when the schema does the heavy lifting.

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's purpose with specific verbs ('Post a delegation request to the blackboard') and resources ('as a 'need' entry with capability requirements'), and distinguishes it from siblings by focusing on delegation rather than other operations like querying, archiving, or summarizing.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like twining_handoff or twining_post, nor does it mention prerequisites or exclusions. It only states what the tool does, not when it should be selected.

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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