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workorai

by io.github.work0r-ai

Create job

employer.create_job

Parse raw text via Gemini AI and create a DRAFT job under the current employer. Synchronous: latency 5-30s. The agent can then call employer.update_job to refine fields and employer.publish_job to make it live.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
apiKeyNoOptional WorkorAI MCP key for in-session authentication when the MCP client was initialized anonymously.
rawTextYesFree-form job description (up to 10000 characters). Parsed by Gemini AI; the call typically takes 5-30 seconds. On a client-side timeout, recover by calling employer.list_jobs with status=DRAFT and pick the most recent row.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNo
jobNo

TDQS

A4.6/5.0
Behavior4/5

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

Discloses key behaviors: synchronous operation, 5-30s latency, creates a DRAFT, uses Gemini AI, and offers a recovery workflow. Lacks details on authorization or failure modes beyond timeout, but overall strong for no annotations.

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 sentences: first defines purpose and behavior, second gives usage guidance. Front-loaded with key info, no wasted words.

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?

Covers purpose, behavior, recovery, and next steps. Existence of output schema reduces need for return value explanation. Minor gap: no mention of error handling for Gemini parsing failure, but acceptable.

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?

Adds meaningful context beyond the schema: rawText is free-form up to 10000 chars parsed by Gemini with recovery on timeout; apiKey is for optional in-session authentication. With 100% schema coverage, the baseline is 3, and this description adds value.

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?

Clearly states the action: parse raw text via Gemini AI and create a DRAFT job under the current employer. Distinguishes from sibling tools by mentioning the DRAFT status and referencing employer.update_job and employer.publish_job.

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?

Provides explicit guidance on when to use this tool (to create a draft) and when to use alternatives (update_job to refine, publish_job to make live). Also includes recovery instructions for client-side timeout.

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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TDQS

A3.8/5.0
Disambiguation5/5

Every tool in the candidate and employer sets targets a distinct action or resource with no ambiguity. Tools like `search_candidates_by_query` and `search_candidates_for_job` have clearly different purposes, and all other tools perform unique operations.

Naming Consistency5/5

All tools follow a consistent `domain.action` pattern with snake_case action names. The naming is uniform across both candidate and employer tools, using standard verbs like get, list, create, update, delete, search, set, etc.

Tool Count4/5

29 tools cover two distinct user roles (candidate and employer) with separate workflows. While above the typical 3-15 range, each tool serves a specific purpose and the count is justified for a hiring platform's API surface.

Completeness4/5

The tool surface provides comprehensive CRUD and lifecycle operations for jobs, applications, invitations, and candidate searches for both roles. Minor gaps like candidate profile update tools are likely handled outside the MCP server, so the set feels nearly complete.

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