roTEAMnet — Global Job Search & Employer Discovery

get_market

Read-onlyIdempotent

Read a cached market snapshot: total active postings, company count and generated_at (UTC). Missing snapshot fields are omitted; this is not a real-time search or a count of unique real-world positions. No arguments, AI call or credits. Use search_jobs for listings and get_job for full details. Required scope: jobs:read

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": "get_market"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description
`total`	No	Active posting count in the generated snapshot.
`companies`	No	Company identities in that snapshot.
`generated_at`	No	UTC snapshot generation timestamp.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 29, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": false,
+  "properties": {
+    "companies": {
+      "description": "Company identities in that snapshot.",
+      "type": "integer"
+    },
+    "generated_at": {
+      "description": "UTC snapshot generation timestamp.",
+      "type": "string"
+    },
+    "total": {
+      "description": "Active posting count in the generated snapshot.",
+      "type": "integer"
+    }
+  },
+  "type": "object"
+}

First observedOct 28, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Goes well beyond the readOnly/idempotent annotations by disclosing the caching model, that missing snapshot fields are omitted, that values are not real-world unique positions, that it costs no AI call or credits, and that it requires the jobs:read scope. These are exactly the behavioral facts an agent needs to interpret stale-looking output correctly.

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?

Front-loads what is returned, then caveats, then alternative tools and required scope. Every sentence carries distinct information with no repetition of schema or annotation content.

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 zero-argument read tool with an output schema and full annotations, the description covers the semantics of the returned fields, staleness, cost, and auth scope. Nothing an agent needs to call or interpret it 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?

The tool takes zero parameters, so the baseline is 4; the description confirms 'No arguments', which is consistent with the empty schema but adds nothing further to specify.

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 ('Read a cached market snapshot') plus the exact fields returned (total active postings, company count, generated_at). It explicitly contrasts itself with search_jobs and get_job, so an agent can distinguish it from siblings without opening a schema.

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 explicit routing: 'Use search_jobs for listings and get_job for full details', plus negative guidance that this is not a real-time search or position count. The only condition for using this tool, wanting aggregate cached market stats, is unambiguous.

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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