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Search JobSlop (ChatGPT connector)

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Read-onlyIdempotent

Search tracked US job listings by keywords such as role, company or location. Returns ids to pass to fetch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch words, e.g. "Stripe data engineer remote".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds one genuine behavioral fact beyond annotations — that the result is a set of ids intended for fetch — but says nothing about result caps, ranking, or empty-result behavior.

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?

Two short sentences, zero filler, and the core action plus the downstream chaining hint are front-loaded. Nothing to cut.

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

Completeness4/5

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

For a one-parameter, read-only search with no output schema, the description supplies what the schema cannot: the resource scope and the id-return contract that feeds fetch. Minor gap is any hint about result volume or pagination, but little else 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%, so the baseline is 3, but the description goes slightly beyond the schema's single example by naming the semantic categories the free-text query should carry (role, company, location), which helps an agent compose a combined keyword string.

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 (search) and resource (tracked US job listings) plus the searchable facets (role, company, location). It is clear on its own, but it never distinguishes itself from the near-identically named siblings jobslop_search_jobs or search-like jobslop_find_job_by_url.

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?

Implied usage only: the phrase 'Returns ids to pass to fetch' tells the agent this is a first step in a two-call chain. However, with three search-flavored siblings there is no explicit when-to-use-this-vs-those guidance and no exclusions.

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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