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Check whether a request fits

check_request
Read-onlyIdempotent

Describe what the user wants in plain words and get back whether this server can do it, which limits it would hit, and the closest thing it CAN do. Instant, no solve. Use it when unsure the tool fits (shift swaps, payroll, time clocks, very large teams or long horizons).

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": {
      "description": "<description>"
    },
    "name": "check_request"
  }
}

Input Schema

NameRequiredDescriptionDefault
descriptionYesThe user's request in their own words, e.g. 'rota for 80 nurses over 3 months with shift swaps'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive behavior, so the safety profile is covered. The description adds meaningful context beyond that: it is instant, performs no solve, and returns limit diagnostics plus a nearest-alternative suggestion, so the agent knows this is a cheap pre-flight probe rather than a commitment.

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?

Two sentences, front-loaded with what comes back, then when to call it. 'Instant, no solve' is terse and slightly cryptic out of context, but no sentence is wasted.

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?

For a single-parameter, read-only probe with no output schema, the description covers the input intent, the three return elements, the cost profile, and the triggering scenarios. Nothing an agent needs in order to call it correctly is missing.

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?

Schema coverage is 100% and includes a worked example, so the baseline is 3. The description still adds value by stressing the parameter is the user's request in plain, natural language rather than a structured spec, and by listing the complexity axes (team size, horizon) the free-text should convey.

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?

States a concrete verb pair (describe a request in plain words, get back feasibility) and enumerates the three-part answer: can it be done, which limits would be hit, and the closest supported alternative. This clearly separates it from build_shift_roster, which actually produces a roster.

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?

Explicitly says to use it when unsure the tool fits, and gives concrete triggering conditions (shift swaps, payroll, time clocks, very large teams, long horizons). It does not explicitly name a fallback sibling such as build_shift_roster, so the when-not path is only implied by 'closest thing it CAN do'.

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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