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company-jobs-feed

company-jobs-feed

Official

Get live jobs from one ATS board (free)

jobs_get_board
Read-onlyIdempotent

Fetch every current job from one company's official Greenhouse, Lever, or Ashby board by ATS and slug, then filter locally by title, location, remote, country, or age.

Instructions

WHAT: Fetch every job currently published on ONE company board from its official public ATS API (Greenhouse, Lever or Ashby), normalize it and filter it locally. WHEN: You know the board (ats + slug), e.g. from jobs_find_board or a careers-page link, and want its live openings now. WHEN NOT: Many companies at once, history (new/closed/reposted since last run), or careers-page discovery at scale: use jobs_search_companies (paid). Unknown board: use jobs_find_board first. SmartRecruiters, LinkedIn, Workday, Workable and Recruitee are not supported and never contacted. BEHAVIOR: Runs on your machine; one GET to the documented API host only (very large Greenhouse boards: a second, lighter GET). Nothing stored, no history: first_seen_at = now and change = null. Any HTTP 403/429 stops that host for the session (kill switch, HOST_BLOCKED error). Lever requests are spaced 1 s apart (its robots.txt Crawl-delay). COST: No APIFY_TOKEN, no billing. RETURNS: Paged "job" rows. compensation only when the ATS publishes it; posted_at is the ATS date or null (never guessed); age_basis says how age_days was derived. PARAMETERS: All filters are AND-ed; values inside one filter are OR-ed. titleIncludes/titleExcludes match whole words ("engineer" does not match "Engineering"). countries uses the ATS's structured country where present (Lever, Ashby) and a place-name list otherwise; rows without any country are dropped when countries is set. postedWithinDays drops rows with posted_at = null. Paging re-fetches the board, so pages from different calls can shift if the employer edits the board in between. EXAMPLE: {"ats":"ashby","slug":"ramp","titleIncludes":["engineer"],"remote":"only"} -> remote engineering roles at Ramp with salary ranges.

Input Schema

NameRequiredDescriptionDefault
atsYesRequired. The applicant-tracking system hosting the board: "greenhouse" | "lever" | "ashby". Example: "ashby"
slugYesRequired. Board slug as it appears in the public board URL (case-insensitive): boards.greenhouse.io/{slug}, jobs.lever.co/{slug}, jobs.ashbyhq.com/{slug}; 1-100 chars: a letter or digit, then letters, digits, ".", "_" or "-". Example: "ramp" or "palantir"
limitNoOptional page size, integer 1-500, default 50
offsetNoOptional items to skip, integer >= 0, default 0; pass nextOffset from the previous response
remoteNoOptional, "any" | "only" | "exclude", default "any"
countriesNoOptional ISO-3166 alpha-2 codes, any-of, case-insensitive. Example: ["US","DE"]
locationsNoOptional, 0-50 strings, any-of. Substring match on location text; "remote" also matches ATS remote flags. Example: ["new york","berlin"]
longOpenDaysNoOptional integer, default 60: rows older than this get long_open = true (a heuristic, not proof of a ghost job)
titleExcludesNoOptional, 0-50 strings, any-of. Drop titles containing any of these. Example: ["intern","manager"]
titleIncludesNoOptional, 0-50 strings, any-of. Keep titles containing any of these whole words/phrases, case-insensitive. Example: ["engineer","data scientist"]
postedWithinDaysNoOptional integer 1-3650: keep jobs whose ATS publish date is at most this many days old. Example: 14
includeDescriptionNoOptional boolean, default false. true adds description_text (plain text, <= 20,000 chars, e-mails/phones removed)

Output Schema

NameRequiredDescriptionDefault
metaNoTool-specific context: board totals, request counts, cost notes
countYesNumber of items in this page
itemsYesResult rows. Each has "type": "job" (job_key, title, company, locations, countries, remote, posted_at, verified_open_at, age_days, long_open, apply_url, source_url, ...), "board", "company", "seed_board", "open_check" or "error" (code, message, retryable)
totalYesTotal items after filters, before paging
offsetYesOffset of the first item in this page
hasMoreYesTrue if more items exist after this page
nextOffsetYesOffset to pass for the next page, or null when done

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.0.5
    • changedInput schema / properties / slug / description
      Previous value: -"Required. Board slug as it appears in the public board URL (case-insensitive): boards.greenhouse.io/<slug>, jobs.lever.co/<slug>, jobs.ashbyhq.com/<slug>. Example: \"ramp\" or \"palantir\""New value: +"Required. Board slug as it appears in the public board URL (case-insensitive): boards.greenhouse.io/{slug}, jobs.lever.co/{slug}, jobs.ashbyhq.com/{slug}; 1-100 chars: a letter or digit, then letters, digits, \".\", \"_\" or \"-\". Example: \"ramp\" or \"palantir\""
  2. First observedv1.0.1

TDQS

A4.9/5.0
Behavior5/5

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

Annotations cover read-only/idempotent/open-world safety, but the description adds substantial context beyond them: runs locally, one GET to the documented host (a second for very large Greenhouse boards), nothing stored so first_seen_at=now and change=null, a HOST_BLOCKED kill switch on 403/429, and 1 s spacing on Lever per robots.txt. It also flags that paging re-fetches the board, so page windows can shift.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Labeled sections (WHAT/WHEN/WHEN NOT/BEHAVIOR/COST/RETURNS/PARAMETERS/EXAMPLE) make it heavily front-loaded and skimmable, and every sentence carries operational content. It is nonetheless a dense block of text for a single-board fetch tool, where a slightly tighter PARAMETERS section would have sufficed.

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 12-parameter, open-world read tool with an output schema, the description covers everything an agent needs: cost (no APIFY_TOKEN/billing), return shape (paged 'job' rows, compensation only when published, posted_at never guessed, age_basis), filter interaction rules, and failure modes. No meaningful gap remains.

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

Parameters5/5

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

Schema coverage is 100%, so the schema documents the fields, yet the PARAMETERS block adds cross-parameter meaning the schema cannot express: filters are AND-ed while values within a filter are OR-ed, titleIncludes/titleExcludes match whole words ("engineer" does not match "Engineering"), countries uses structured country where present and drops rows lacking one, and postedWithinDays drops rows with posted_at=null.

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?

The WHAT line states a specific verb+resource+scope: fetch every job on ONE company board from its official public ATS API, then normalize and filter locally. It explicitly names the supported ATSs (Greenhouse, Lever, Ashby) and the unsupported ones, 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?

The WHEN/WHEN NOT blocks are explicit: use when you know ats+slug; use jobs_find_board when the board is unknown, and jobs_search_companies (paid) for many companies, history, or careers-page discovery at scale. It also names unsupported providers that are never contacted, removing ambiguity entirely.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.