Zooq

g_skill_lookup

Read-onlyIdempotent

Resolve one skill by its stable skl_ id — returns the display name and normalized name. Get the id from g_title_skills_lookup (skill search). (Costs 10 Zooq credits.)

Input Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes	Stable skill id (skl_...). Get it from g_title_skills_lookup — read data[].id.

Output Schema

TableJSON Schema

Name	Required	Description
`id`	No	Example value was a string
`name`	No	Example value was a string
`normalized_name`	No	Example value was a string

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds the 10-credit cost, which is not captured in annotations, and clarifies that the result is a single skill's display and normalized names. This is meaningful extra context beyond the annotations.

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 two short sentences plus a parenthetical, with no filler. It front-loads the core action, then provides the id source and the cost. Every word adds value.

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 single-parameter, read-only tool with a complete schema and an output schema, this description covers everything an agent needs: what it does, where the input comes from, and the cost. Nothing is missing for a correct invocation.

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 coverage is 100% and the schema already describes the id parameter, including its format and how to obtain it. The description repeats the same information without adding new semantic detail, so it stays at the baseline for fully covered parameters.

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 description states a specific verb ('resolve'), a resource ('one skill'), and the input format ('stable skl_ id'), and it names the sibling g_title_skills_lookup as the source for that id. This clearly distinguishes it from the search tool and tells an agent exactly what the operation does.

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?

It explicitly says to get the id from g_title_skills_lookup, establishing the prerequisite workflow and effectively stating when to use this tool (after a search). The mention of the 10-credit cost also helps an agent decide if the operation is worth running.

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

A3.6/5.0

Disambiguation2/5

Many tools have strongly overlapping purposes: companies_name_lookup is explicitly equivalent to search_companies, companies_enrich/companies_info/companies_universal_name_to_id all return company-profile data, and profile_full overlaps with profile_employment_history and profile_enrich. The descriptions are detailed, but an agent would still frequently have to choose between near-duplicate endpoints.

Naming Consistency4/5

Tool names mostly follow a predictable resource-prefixed snake_case pattern, such as companies_*, jobs_*, posts_*, profile_*, and search_*, which makes the set readable and groupable. Minor inconsistencies like jobs_details_v2, g_title_skills_lookup, and mixed noun suffixes (info/details/full/lookup) keep it from a perfect score.

Tool Count2/5

44 tools is well beyond the heavy 25+ band, and several tools appear to be different lookup modes or near-duplicates of the same underlying capability. The broad LinkedIn-style data domain explains much of the size, but the set still feels bloated rather than well-scoped.

Completeness4/5

The API covers the core read-only professional-data workflows well: people, companies, jobs, posts, comments, likes, email discovery/verification, schools, skills, and targeted searches. Minor gaps exist, such as some job filters being unusable and no direct exposure of certain profile alias endpoints, but agents can generally complete end-to-end workflows.

Resources

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