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Social Fetch

by io.github.social-freak-ltd

Search LinkedIn jobs

linkedin_jobs_search_list
Read-only

Search LinkedIn jobs by keyword and filters. Returns a list (use cursor when paginated).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum job listings to return (default 10).
remoteNoOptional work arrangement filter.
companyNoOptional company name filter.
countryNoOptional ISO 3166-1 alpha-2 country code, e.g. "GB" or "US". Narrows an ambiguous `location` label to one country; leave unset when `location` is already a country name.
jobTypeNoOptional job type filter.
keywordYesRequired. Search keyword for LinkedIn job listings — a job title, skill, or company term, e.g. "typescript engineer" or "growth marketer".
locationYesRequired. Location label as you would type it into LinkedIn's location box — a city, region, or country name, e.g. "London", "Greater Seattle Area", or "United Kingdom".
timeRangeNoOptional time range filter for when jobs were posted.
locationRadiusNoOptional location radius filter.
experienceLevelNoOptional experience level filter.

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the description's job is to add context. It discloses return type ('Returns a list') and pagination behavior ('use cursor when paginated'), which goes beyond annotations. No contradiction exists.

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?

The description is one clear sentence plus a short pagination hint, both front-loaded and free of filler. Every word contributes either to purpose or to behavioral guidance.

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?

For a tool with 10 parameters (5 enums) and no output schema, the description could be expected to explain more about response semantics. However, it does state return type and pagination, and the parameter schema is thorough. The description is adequate given the schema's richness, though it omits details like how filters combine.

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%, so the schema already documents every parameter in detail. The description's phrase 'by keyword and filters' only summarizes parameters without adding new meaning. It does not compensate for any gaps since no gaps exist.

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 clearly states the tool searches LinkedIn jobs with keyword and filters, and returns a list. It is specific enough to distinguish from sibling tools like linkedin_people_search_list, though it does not explicitly contrast with linkedin_jobs_get. The name also reinforces the search-list behavior.

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

Usage Guidelines3/5

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

The description implies usage (search for jobs) but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. The note 'use cursor when paginated' is a usage hint but not about tool selection. Guidance is only implicit.

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

B3.4/5.0
Disambiguation5/5

Each tool is clearly scoped to a specific platform and action (e.g., facebook_post_get vs instagram_post_get). Descriptions explicitly differentiate similar tools across platforms, and within-a-platform tools like tiktok_search_videos_list vs tiktok_search_hashtag_list have clear disambiguation notes.

Naming Consistency5/5

All 167 tools follow a strict `platform_resource_action` pattern (e.g., youtube_video_comments_list). No mixing of styles—snake_case throughout, with consistent verb ordering (get, list, search, etc.).

Tool Count2/5

The server has 167 tools, which is far beyond the typical well-scoped range of 3-15. While the broad multi-platform scope justifies many tools, this extreme number makes the tool surface overwhelming and difficult for an agent to navigate efficiently.

Completeness4/5

The tool set covers a wide range of platforms and operations including profile retrieval, post/video fetching, comments, search, transcripts, and ad library access. Minor gaps exist (e.g., no Facebook events or LinkedIn messaging), but the surface is comprehensive for a read-only data aggregation use case.

Resources