Distil — Machine-Native Public Data Refinery

Search US SEC Companies

search_us_companies

Read-onlyIdempotent

Searches US public corporations by stock ticker symbol or company name against official SEC EDGAR submissions.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum number of search results to return (default 5, max 20).
`query`	Yes	US ticker symbol or partial company name (e.g. 'Tesla', 'NVDA', 'Pfizer').
`forceFresh`	No	Spend Control: When true, bypasses Edge KV cache and forces a real-time statutory primary registry call (applies 2.5x Freshness Inconvenience Surcharge). Default: false.
`maxAgeHours`	No	Spend Control: Maximum acceptable data age in hours (e.g. 48 for 2 days tolerance). If cache satisfies this, delivers sub-5ms at standard 1.0x Economy rate. Set to 0 to force live primary fetch.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`content`	Yes
`isError`	No

TDQS

A3.8/5.0

Behavior3/5

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

The annotations already cover readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is handled elsewhere. The description adds the useful context that the search targets official SEC EDGAR data, but it does not disclose other behavioral traits like pagination, result ordering, or cache/spend behavior beyond what the schema already exposes.

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?

A single, front-loaded sentence conveys the essential purpose without any wasted words. It is appropriately sized for a search tool and does not repeat schema or annotation details.

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?

Given the low complexity, fully documented schema, rich safety annotations, and existing output schema, the description provides enough context for an agent to select and invoke the tool correctly. It could be marginally stronger by explicitly directing filing-specific requests to get_us_sec_filing, but that is covered by the sibling naming and overall context.

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 all parameters, including query, limit, forceFresh, and maxAgeHours. The description restates the core query semantics but adds no new meaning beyond the structured 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?

The description uses a specific verb ('Searches'), names the resource ('US public corporations'), and specifies the query dimensions ('stock ticker symbol or company name') against 'official SEC EDGAR submissions.' It clearly distinguishes this search tool from filing-retrieval and non-US siblings.

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 the tool should be used when an agent needs to find US public companies by ticker or name, and the sibling names reinforce that this is the US company search. However, there is no explicit when-to-use/when-not-to-use guidance or mention of alternatives such as get_us_sec_filing for retrieving specific filings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Distil — Machine-Native Public Data Refinery tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0

Disambiguation5/5

Each tool maps to a distinct data product: country-specific filings, tender records/search, risk scoring, sanctions screening, and entity graphs. The search/get split cleanly separates discovery from retrieval, and even similar country-specific tools are clearly qualified by region and entity type.

Naming Consistency5/5

All tools use a consistent snake_case verb_noun pattern: get_* for retrieval and search_* for discovery, with country or region qualifiers where applicable. Cross-cutting tools like get_corporate_risk_score and get_tender_intelligence fit the same pattern without feeling out of place.

Tool Count4/5

At 16 tools, the server is slightly above the ideal 3-15 range, but the multi-country, multi-domain scope justifies nearly every tool. The set is heavier than a tightly focused server, yet no tool feels redundant.

Completeness4/5

The set covers the core read-only workflow well: search to find entities or tenders, get to retrieve records, plus analytical tools for risk, sanctions, and tender intelligence. Minor gaps exist, such as no Spanish company registry access and no UK tender search, but these are workable and do not block primary due-diligence workflows.

Resources

Need Help?