Resume Booster Job Board

Score a résumé against the board

fit_resume

Read-onlyIdempotent

Score a résumé against open jobs, for an agent holding a CV: reads the occupation out of resumeText (or uses query if given), searches the board for it, and scores up to 20 results 0-100 with the matched and missing terms per job. PAID — needs a paid API key, exactly like POST /v1/fit on the data API, or a live Agent Pass on the key's account; a free key gets an in-band refusal naming where to upgrade. A null fit means the posting has no stored description to score. Returns the terms it read from the CV so the agent can pick a different one and call again with query. Needs a key or a sign-in.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Jobs to score, 1-20 (default 20).
`query`	No	Optional job title to search instead of the one read from the résumé.
`remote`	No
`country`	No
`location`	No
`resumeText`	Yes	The candidate's résumé as plain text (100+ characters).

Output Schema

TableJSON Schema

Name	Required	Description
`jobs`	Yes
`note`	No
`query`	No	What was actually searched. Null when no occupation was recognised.
`terms`	Yes	The occupations read out of the résumé, best first.
`total`	No	Exact match count. ABSENT with countUnavailable:true when the board refuses to guess.
`hasMore`	No
`didYouMean`	No
`nextOffset`	No	Pass back as `offset` for the next page.
`excludedTerms`	No
`intentFilters`	No	Words read out of the query as filters.
`ignoredFilters`	No	Filters the board could NOT apply. Results answer a wider question than was asked.
`agenciesExcluded`	No	Row-selecting: disclosed agency inventory is hidden from this page.
`countUnavailable`	No	The board could not count this query exactly — do not report a total.
`salaryStatedOnly`	No	Row-selecting: this page excludes the ~76% of postings with no annualised figure in approximate US dollars (2026-09-27), including postings that publish an hourly rate.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedSep 27, 2026

changedOutput schema / properties / jobs / items / properties / workMode / description

Previous value: -"Stated or inferred from title/location; null when neither says."New value: +"The employer's own statement: the option they chose in their ATS, or their own words on the posting (title, location, department). null has THREE meanings: neither source says anything, the two disagree and the board refuses to choose, or the posting is older than the vendor field this board now reads. Never inferred from the description, and silence is never read as onsite."

changedOutput schema / properties / salaryStatedOnly / description

Previous value: -"Row-selecting: this page excludes the ~87% of postings with no stated pay."New value: +"Row-selecting: this page excludes the ~76% of postings with no annualised figure in approximate US dollars (2026-09-27), including postings that publish an hourly rate."

First observedSep 18, 2026

TDQS

A4.3/5.0

Behavior5/5

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

With annotations already covering read-only/idempotent/no-destructive, the description adds genuinely new behavior: PAID access requiring a paid key or Agent Pass, an in-band refusal for free keys naming where to upgrade, and the meaning of a null fit. This is exactly the value-add beyond structured fields.

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?

Front-loaded with the purpose and workflow, then the paid/auth caveat and return semantics. It is dense and slightly run-on with stacked parentheticals, but each clause carries information an agent needs.

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?

An output schema exists, so return values need not be re-explained, yet the description still notes the returned terms and the null-fit case. Auth requirements, pricing, and refusal behavior are all covered — nothing an agent needs to invoke this correctly 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 only 50% (remote, country, location undocumented), so the description carries extra burden. It adds real meaning for resumeText (plain text, 100+ chars), query (title to search instead of CV-derived one), and the limit=20 cap, but says nothing about remote/country/location filters, leaving a partial gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource ('Score a résumé against open jobs') and elaborates the pipeline (read occupation, search board, score up to 20 results), which clearly separates it from siblings like search_jobs or get_job. It stops short of naming an alternative sibling explicitly, so it lands at a strong 4 rather than a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It scopes the caller ('for an agent holding a CV') and gives a concrete workflow: use resumeText, or pass `query` if you already have a title, and re-call with `query` if the returned terms are wrong. No explicit when-not or named alternative, so 4.

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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