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delegations-mcp

delegations-mcp

by kaijfox
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

run_delegation

Execute predefined delegation prompts to orchestrate tasks between primary and specialized agents, returning execution summaries and transcript paths.

Instructions

Run a delegation by its library:name. Returns summary, prompt_path, transcript_path.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>"
    },
    "name": "run_delegation"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
inputsNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It discloses return values ('summary, prompt_path, transcript_path'), which adds context beyond the input schema, but fails to describe behavioral traits like whether it's read-only, destructive, requires authentication, has side effects, or rate limits. For a tool named 'run', this is a significant gap.

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

Conciseness4/5

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

The description is front-loaded with the main action and resource, followed by return values. It's concise with two clauses, but the second clause could be more integrated; overall, it's efficient with minimal waste.

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

Completeness3/5

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

Given complexity (2 parameters, nested object, no annotations) and an output schema exists, the description is moderately complete. It covers the purpose and return values, but lacks behavioral context and full parameter details. The output schema reduces the need to explain returns, but gaps in usage and transparency remain.

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 0%, so the description must compensate. It adds meaning by specifying the 'name' parameter as 'library:name', clarifying its format, but doesn't explain 'inputs' (a nested object with no details). This partial compensation meets the baseline for low coverage, but leaves 'inputs' undocumented.

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

Purpose3/5

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

The description states the action ('Run a delegation') and resource ('by its library:name'), but it's vague about what 'run' entails—does it execute, simulate, or test? It distinguishes from siblings 'get_delegation' and 'list_delegations' by implying execution rather than retrieval, but the purpose lacks specificity.

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?

No guidance on when to use this tool versus alternatives like 'get_delegation' or 'list_delegations'. It mentions 'by its library:name', hinting at a prerequisite (a delegation must exist), but no explicit when/when-not rules or context for selection are provided.

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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