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Mandate Law: legal counsel for AI products

Request a feature check (may be billed)

feature_check

For engaged clients, with the human's approval (it may be billed). Call before building a change that matches counsel-triggers.json. Do not ship the change until counsel responds.

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": {
      "matter_id": "<matter_id>",
      "matter_token": "<matter_token>",
      "change": "<change>",
      "trigger_ids": "<trigger_ids>"
    },
    "name": "feature_check"
  }
}

Input Schema

NameRequiredDescriptionDefault
changeYes
matter_idYes
trigger_idsYes
matter_tokenYesThe matter_token returned by request_engagement. Keep it secret.
target_ship_dateNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Beyond the annotations, it discloses billing risk, required human approval, engagement eligibility, and the blocking wait for counsel. It still leaves unclear what happens after the request is submitted, such as whether the call returns a pending status and how counsel's response is retrieved.

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 eligibility and approval before the call timing. No wasted wording.

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?

Covers the decision to call and the blocking condition, but for a five-parameter legal request with no output schema it omits how to obtain the trigger IDs, how to confirm counsel's response, and the role of the optional ship date.

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?

With only 20% schema coverage, the description must explain the five parameters but only covers the change and the triggers context indirectly. matter_id, matter_token (documented only in schema), trigger_ids format, and target_ship_date remain unaddressed.

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?

The body says to call before building a change that matches counsel-triggers.json and to wait for counsel, which makes the purpose a counsel feature review. It does not explicitly define 'feature check' or contrast it with siblings such as check_scope, but the action and resource are inferable.

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?

Gives explicit prerequisites (engaged client, human approval, potential billing) and timing (before building a matching change, do not ship until counsel responds). It does not name alternative tools or state what to do for non-matching changes, so it stops short of full routing guidance.

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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