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create_service

Propose a shared service profile and its link to this project. Always requires human admin review, never creates secrets or grants. Requires documents.write and resources.read.

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": {
      "project_id": "<project_id>",
      "name": "<name>",
      "provider": "<provider>",
      "rationale": "<rationale>",
      "evidence": "<evidence>",
      "idempotency_key": "<idempotency_key>"
    },
    "name": "create_service"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
evidenceYes
providerYes
rationaleYes
project_idYes
documentationNo
result_offsetNo
default_purposeNo
idempotency_keyYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations only state write/not-destructive/not-idempotent; the description goes further by disclosing the mandatory human admin review step and the explicit scope limit (no secrets, no grants), which materially changes how an agent should sequence the call. It does not explain the interaction between idempotentHint=false and the required idempotency_key parameter, leaving a small ambiguity.

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 short sentences, front-loaded with the action, each carrying distinct information (what it does, approval requirement, scope limit, permissions). No filler or repetition.

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?

It covers the operational essentials for an approval-gated mutation (permissions, review, scope exclusions), which is more than many tools offer. But with nine undocumented parameters and no output schema explaining what a proposal returns, an agent still lacks enough context to construct a complete correct call.

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

Parameters2/5

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

Schema description coverage is 0% across 9 parameters, so the description must compensate, and it adds no meaning for any of them. Required fields like rationale, evidence, provider, and idempotency_key, plus the unexplained result_offset on a creation tool, are left entirely opaque.

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

Purpose4/5

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

"Propose a shared service profile and its link to this project" gives a specific verb-plus-resource and clarifies the name/title mismatch (create_service is really a proposal). It doesn't explicitly name update_service or list_service_changes as siblings, but the proposal framing distinguishes it from a direct write.

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

Usage Guidelines3/5

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

"Always requires human admin review" tells the agent this lands in an approval queue, and "never creates secrets or grants" bounds what it does, which is useful exclusion guidance. However, it never states when to prefer update_service, request_binding, or the read siblings, so routing still requires inference.

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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