Federal campaign finance activity — PAC committees, total political disbursements, receipts, and political footprint signal. Source: FEC electronic filings. Use for political risk monitoring and PAC compliance. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and destructiveHint, and the description adds beyond that: it names the data source (FEC electronic filings) and discloses the cryptographic attestation with a verification link. This is useful behavioral context.
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?
Three concise, information-dense sentences: what the tool returns, when to use it, and attestation details. No filler or redundancy.
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?
Despite the tool's simplicity (one parameter, read-only), the description omits the meaning of the required parameter, which is essential for invocation. The source and attestation details are helpful but do not compensate for this critical 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 only parameter is 'name,' and schema description coverage is 0%. The description never explains what 'name' refers to (committee? candidate? entity?), leaving the agent without enough information to populate the required field correctly.
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?
Description clearly specifies the tool's domain—Federal campaign finance—with concrete data elements (PAC committees, total political disbursements, receipts, footprint signal). This distinguishes it from sibling tools like get_ofac_sanctions_screening or get_federal_court_cases.
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?
Explicitly states 'Use for political risk monitoring and PAC compliance,' giving clear usage context. However, it does not mention alternatives or when-not-to-use, so it stops short of a 5.
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.
Every tool targets a distinct regulatory domain or data source—from OFAC sanctions to CRA ratings to NIST AI RMF—with clear boundaries. Even the three screening tools (OFAC, OIG, SAM) differ by governing agency and list, and their descriptions explicitly disambiguate them.
All tools follow the consistent lower_snake_case pattern 'get_<domain>_<focus>', such as get_ofac_sanctions_screening and get_us_state_ai_legislation. There are no mixed conventions, vague verbs, or unexpected abbreviations.
18 tools is slightly above the ideal 3-15 range but appropriate for a broad governance data server covering federal, state, and international regulatory sources. Each tool corresponds to a meaningful dataset, so the count feels justified rather than padded.
The surface covers a wide array of governance and compliance domains, including AI regulation, financial enforcement, sanctions, and legal screening, with no critical dead ends for typical lookups. However, it lacks some common regulatory areas (e.g., SEC, HIPAA, GDPR) and offers only read-only access, which is acceptable but not exhaustive.