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by HireLayer
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search_jobs

Find stored open jobs closest to a resume by proximity, returning job IDs, titles, similarity scores (0-1) best first, and whether already scored. No evaluation—use score_resumes to score.

Instructions

Find the user's stored open jobs closest to a resume, by proximity only: job_ids with their title and a similarity between 0 and 1, best first, and whether the resume is already scored for each. No evaluation: score the ones worth it with score_resumes. Give the resume as the application_id of a stored resume or as resume_text (the resume is then stored). Costs 1 HireLayer credit per search.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "search_jobs"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoHow many jobs to return, 10 by default.
workspaceNoThe client company this call belongs to, when the user recruits for several companies: its HireLayer workspace id (letters, digits and . _ : ~ -, up to 200 characters), e.g. acme-corp. Jobs, resumes and scores stay apart from other clients'. A new id creates a new workspace, so reuse the exact id. Omit it for the user's default workspace.
resume_textNoA resume not stored yet, as plain text.
application_idNoA stored resume. Give application_id or resume_text.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.1.0

TDQS

A4.9/5.0
Behavior5/5

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

With annotations present the bar is lower, yet the description adds material that annotations cannot convey: a side effect (resume_text causes the resume to be stored, which explains readOnlyHint=false), a billing cost of 1 HireLayer credit per search, and the return ordering. These are exactly the traits an agent needs before deciding to call.

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 dense sentences with zero filler: scope and return shape first, the alternative and input mechanics next, cost last. Every clause carries information an agent would otherwise have to guess.

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?

No output schema exists, and the description compensates by describing the return shape (ids, titles, similarity range, ordering, scored flag). All four parameters are accounted for and the surprising non-read-only behavior is explained, so nothing critical 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 adds real meaning the schema does not: that application_id and resume_text are alternative ways to supply the same resume, and that supplying resume_text persists it. It does not touch the workspace-isolation or limit parameters, which the schema already handles well.

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 specific verb and resource ('Find the user's stored open jobs closest to a resume') plus the exact scope qualifier 'by proximity only', and enumerates what comes back (job_ids, title, similarity 0-1, best first, already-scored flag). This is clearly distinguishable from score_resumes, which it names as the evaluation step instead.

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?

Gives an explicit when-not ('No evaluation') and routes to the correct sibling ('score the ones worth it with score_resumes'). It also states the two input modes (application_id for an existing resume vs resume_text) and the cost condition, leaving little to inference.

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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