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Search RoleWeek jobs

search_jobs
Read-onlyIdempotent

Searches developer and tech roles that employers posted in the last 7 days, read directly from the employers' own hiring systems (Workday, Greenhouse, Lever, Ashby, iCIMS and others) and checked daily. Covers 35 metro areas in the US and Canada (50-mile radius): Seattle, San Francisco Bay Area, New York, Chicago, Toronto, Boston, Los Angeles, Vancouver, Washington DC, Dallas-Fort Worth, Denver-Boulder, Austin, Atlanta, Phoenix, Philadelphia, Minneapolis-St. Paul, San Diego, Raleigh-Durham, Detroit, Houston, Charlotte, St. Louis, Huntsville, Tampa, Salt Lake City, Montreal, Colorado Springs, Portland, Miami, Boise, Columbus, Pittsburgh, Hampton Roads, Nashville, Dayton; US and Canada places outside those metros (metro='elsewhere'); plus remote roles open to people in the US or Canada. Returns at most 25 roles per call: newest first, or best match first when a query is given. Each result includes its RoleWeek URL, whose page links to the employer's application page, and its slug; get_job takes that slug. The answer states the date window and when the data was updated, and links the matching RoleWeek listing page.

Input Schema

NameRequiredDescriptionDefault
limitNoNumber of roles to return (1-25).
metroNoMetro area (50-mile radius), or 'remote' for roles open to people anywhere in the US or Canada.
queryNoKeywords matched against title, company, skills and location, e.g. 'python', 'Stripe', 'rust kubernetes'. Every word must match.
skillNoTechnology the role must list, by name: 'Rust', 'Python', 'Kubernetes', 'C++', 'Go' (nicknames such as golang or k8s work). Several names: the role must list every one. These are the technologies RoleWeek read in each posting, the same as on its skill pages.
seniorityNoOne or more levels; entry = junior/new grad, staff-plus = staff, principal and above.
work_modeNoOnly roles whose listing states this work mode (a role flagged remote counts as remote only, as on the site). Roles that state none are left out.
min_salaryNoYearly salary in the role's currency (USD in the US, CAD in Canada). Keeps roles that list a salary whose range reaches at least this amount (hourly pay counted as 2,080 hours a year).
role_familyNoRole family. 'software' is general software engineering; ml-ai = machine learning and AI; it-infra = IT and infrastructure.
no_account_neededNotrue: only roles whose hiring system RoleWeek checked and found the application form opens on the employer's own site with no account to create. Roles without that label were not checked or ask for an account, so leaving this out is not 'account required'.
posted_within_daysNoOnly roles posted within this many days (1-7).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent and closed-world, so the safety profile is covered. The description adds genuinely useful behavior beyond that: a hard cap of 25 results per call, ordering rules (newest first, best-match when a query is given), daily freshness checking, and that the answer states the date window and update time.

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

Conciseness3/5

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

The opening clause is well front-loaded, but the full enumeration of 35 metro names duplicates the schema's enum verbatim and consumes most of the text. Removing that list would make the definition materially tighter without losing information.

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?

With no output schema, the description still explains the return shape: count cap, ordering, per-result URL and slug, plus the metadata about date window and update time. Nothing an agent needs to call this correctly is missing.

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

Parameters3/5

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

Schema description coverage is 100% and enum values are fully documented, so the schema does the heavy lifting. The description only adds ordering semantics and the 25-result cap, and it redundantly re-lists all 35 metros already enumerated in the schema.

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 (searches developer/tech roles) with sharp scope: last 7 days, read from employers' own hiring systems, 35 metros plus remote. An agent can immediately distinguish this from get_job and the summary siblings.

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?

The description makes clear this is the discovery/listing step and that get_job takes the returned slug, which routes the agent between the two tools. It lacks an explicit statement of when-not-to-use (e.g., versus weekly_summary or salary_summary), so it stops short of full routing guidance.

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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