Extract structured job details—company, requirements, responsibilities—from a job posting URL. Use it to parse LinkedIn, Greenhouse, Lever, Ashby, or Wuzzuf listings into actionable data.
Scrape and extract structured job description, company name, requirements, and responsibilities from a job URL (LinkedIn, Greenhouse, Lever, Ashby, Wuzzuf).
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL of the job posting. |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It usefully discloses a scope constraint by naming supported sources (LinkedIn, Greenhouse, Lever, Ashby, Wuzzuf), which hints at failure modes for unsupported sites, but it omits auth requirements, rate limits, and whether the scrape is live/network-dependent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single efficient sentence with the core action front-loaded and the output fields enumerated compactly. The parenthetical platform list is slightly dense but earns its place by defining scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool with no output schema, the description adequately covers both the input (job URL) and the expected return (job description, company, requirements, responsibilities). Only the platform-failure behavior remains unaddressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There is a single parameter whose schema description coverage is 100%, so the baseline is 3. The description adds only the notion that the URL points to a job posting and implies platform compatibility, but gives no syntax or format detail beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (scrape and extract) plus the resource (structured job data from a job URL) and enumerates the extracted fields. It is clearly distinct from siblings like civify_parse_cv, civify_tailor_cv, and civify_score_ats, which operate on CVs rather than job postings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied: an agent can infer it applies when it holds a job posting URL. There is no explicit when-to-use vs. when-not-to-use guidance, no prerequisites, and no mention of what to do with an unsupported URL even though the tool names specific supported platforms.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.