searchnapply

This connector has been deprecated

Deprecated.

Show chosen job postings

job_postings_search_widget_render

Read-onlyIdempotent

Purpose: Show postings as an interactive list in a chat app such as ChatGPT or Claude; a gone posting is listed in dropped. When: After job_postings_search in a chat app, unasked; in a terminal write text instead; monitor_get and monitor_review_widget_render cover a monitor. Cost: About 170 tokens per posting.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "ids": [
        4711,
        4712
      ],
      "found": 120
    },
    "name": "job_postings_search_widget_render"
  }
}

Input Schema

Name	Required	Description	Default
`ids`	Yes	Ids of the postings to show, 1 to 100, from the user's recent search, in the order to show them.
`found`	Yes	How many postings that search matched in total.

Output Schema

Name	Required	Description
`rows`	Yes	The chosen postings, one summary each, in the order asked for.
`found`	Yes	How many postings the search matched in total.
`search`	No	The newest kept search that still holds any of the chosen ids; absent when none does.
`dropped`	Yes	The chosen ids that could not be shown.
`departments`	Yes	That search's department facets; empty when it had none or no kept search answered.

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 9, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, open-world and non-destructive, so the safety profile is covered. The description adds genuinely new behavior: unavailable postings appear in a "dropped" output, and rendering costs roughly 170 tokens per posting, which lets an agent budget context. It stops short of any limits on batch size or failure modes, so it is strong but not exhaustive.

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 labeled lines (Purpose/When/Cost) front-load the essential routing information with no filler. Every clause carries actionable information, and the token cost is placed last where it reads as a decision aid rather than a lead-in.

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?

An output schema exists and covers return values, so the description needn't explain them. Combined with annotations covering safety and the explicit sibling routing, an agent has everything needed to decide whether to render and how to call it.

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

Parameters3/5

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

Schema coverage is 100%: both parameters are already documented, including the 1-100 range, the source of ids, the display ordering, and what found means. The description adds no syntax, formatting, or constraint detail beyond that, so the baseline 3 applies.

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?

"Show postings as an interactive list in a chat app such as ChatGPT or Claude" names a specific verb and resource plus the rendering surface, and the dropped-posting clause clarifies what the list may contain. It also implicitly separates this render tool from the sibling monitor_review_widget_render by naming that sibling for a different scope.

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

Usage Guidelines5/5

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

The "When" line gives explicit triggering conditions (after job_postings_search, unsolicited in a chat app), an explicit when-not (in a terminal, write text instead), and names the alternatives that cover monitors. An agent does not need to infer any of this.

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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