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datasets_jobs_company_item

Fetches a company by dataset board id, returning LCA sponsorship filing counts and tech stack hints when available. Returns 404 if the board id is not registered.

Instructions

Get a single company by board id. Returns one discovered company board by its dataset board id. When the company name matches recent public U.S. Department of Labor LCA disclosure data, the response includes lca_sponsorship with filing counts and observed fiscal-quarter range; this is company-level historical evidence, not a guarantee for a specific role or candidate. When the board carries a known domain, the response also includes a tech_stack firmographic hint. Returns 404 when the board id is not in the registry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesDataset board id
Behavior5/5

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

With no annotations, the description fully carries the transparency burden. It discloses the 404 error case, the conditional lca_sponsorship enrichment and its limitations, plus the tech_stack hint when a domain is known. This goes well beyond basic read-only behavior.

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 three sentences, front-loaded with the main purpose, and each sentence provides essential context (enrichments and error handling). No fluff or redundancy.

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?

Despite no output schema, the description covers the base return (company board), conditional enrichments, and failure mode (404). This is sufficient for a simple one-parameter lookup tool, especially given the clarity of the response structure.

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%, so the baseline is 3. The description reinforces that 'id' refers to a board id but doesn't add new details like format, examples, or the source of the id. It meets the minimum bar but doesn't exceed it.

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 clearly states 'Get a single company by board id' with a specific verb and resource. It immediately distinguishes itself from related tools like datasets_jobs_companies (list) or datasets_jobs_search by specifying the retrieval-by-ID nature.

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 implies usage context: when you have a board id and want company-level details. It does not explicitly name alternatives or exclusions, but it clearly communicates that this is for a single lookup, differentiating it from search/list tools.

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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