sec_companyOne-call SEC snapshot of a US public company: recent filings, indexed events, insider activity, key XBRL facts (revenue, income, cash). $0.02/call.
| Name | Required | Description | Default |
|---|---|---|---|
| cik | No | ||
| ticker | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safe-read profile is covered. The description adds useful context about the data categories included and the per-call cost, but it does not disclose operational behavior such as identifier requirements, recency bounds, or pagination. This is acceptable but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that packs in the resource, the included data categories, and the cost. There is no filler, and every part contributes to selection and invocation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the description does not need to explain return values. It gives a reasonable outline of the snapshot contents, but it leaves unclear how to specify the company when both parameters are optional. Basic invocation is inferable from the property names, so this is adequate but has a clear gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It only says 'US public company,' which implies the cik and ticker identify such a company, but it does not explain whether one is required, whether they are interchangeable, or what happens when both are null. The parameter names are self-explanatory, but the description adds little beyond them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the resource (a US public company) and the kind of output (a snapshot combining filings, events, insider activity, and XBRL facts). It is specific and informative, though it lacks an explicit verb like 'get' or 'retrieve' and does not directly contrast itself with the sibling sec_events tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to prefer this tool over alternatives such as sec_events, or what kind of request should use this aggregate snapshot. The phrase 'One-call' implies convenience, but it never states when this is the right choice versus a more specialized tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly separated by domain or action (credit, products, regulations, SEC, technology). The three technology tools could be confused at first glance, but their descriptions differentiate a ranked scan, a single-topic snapshot, and an on-demand deep analysis well.
Tool names follow a predictable lowercase snake_case pattern using noun phrases like credit_balance, funding_signals, and sec_events. The single deviation is list_products, which uses a verb_noun form, but the overall style remains consistent and readable.
Nine tools is well-scoped for a multi-domain intelligence API covering account balance, product catalog, funding, regulations, SEC data, and technology research. Each tool represents a distinct product offering without unnecessary sprawl.
The tool set covers the advertised product surface well, including account management, product discovery, and four data verticals. Minor gaps exist, such as no bulk funding search or regulatory detail drill-down beyond the provided signals, but agents can accomplish core workflows without dead ends.