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HumanEndpoint

Get human quote status

human_get_quote

Poll a human-reviewed quote. When status=offered, inspect the operator's service fee, expense authority and expiry. Creating the job accepts those terms. When declined, inspect the reason before deciding whether to resubmit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
quote_idYes
quote_tokenYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior4/5

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

No annotations exist, so the description carries the full burden, and it does meaningfully disclose behavior: it is a polling operation, results are status-dependent, and 'creating the job accepts those terms' warns of a consequential downstream action implied by the returned terms. It omits auth expectations for the quote_token and any token expiry/polling-rate behavior.

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?

Three sentences, front-loaded with the core purpose, then status-conditional guidance with no filler. Efficient, though the two conditional clauses could be tightened slightly.

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?

With no annotations and no output schema, the description does a fair job of framing the status-dependent return semantics and the consequential creation step. However, it leaves both required parameters and the authentication model unexplained, which is a real gap for a 2-required-param tool.

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% and neither quote_id nor quote_token is documented in the schema. The description never explains what these parameters are or where the token comes from, so it fails to compensate for the coverage gap.

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?

States a specific verb+resource: 'Poll a human-reviewed quote.' That is clearly distinct from siblings like human_request_quote (which creates the quote) and human_get_job. It does not explicitly name those siblings, so it stops short of a 5.

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?

The description tells the agent what to do with each status value (offered -> inspect fee/expiry, declined -> inspect reason), which is implied usage guidance. But it never states when to call this tool in the first place (e.g. after human_request_quote) nor when to prefer a sibling such as human_get_job.

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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