reg_rulesTrack US federal rules and proposed rules from the Federal Register by term/agency/significance, with deadline flags (comments_close_soon, effective_soon) and day counts. $0.005/call. Not legal advice.
| Name | Required | Description | Default |
|---|---|---|---|
| term | No | ||
| limit | No | ||
| since | No | ||
| types | No | rule,proposed_rule | |
| until | No | ||
| agency | No | ||
| significant_only | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnlyHint=true and destructiveHint=false. The description adds beyond that: deadline flags (comments_close_soon, effective_soon), day counts, per-call cost, and a non-legal-advice disclaimer. No contradiction exists.
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 compact and front-loaded: main action first, followed by key output features, then cost and legal disclaimer. No filler or repetition; every clause adds useful information.
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 and read-only annotations, the return-format and safety concerns are covered. However, the 0% schema coverage means the description needs to explain filter parameters more fully; missing since/until/types/limit leaves meaningful gaps for a 7-parameter tool.
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?
Schema description coverage is 0%, so the description must compensate. It explains term, agency, and 'significance' (significant_only), but says nothing about since, until, types, or limit—four of the seven parameters. The date-range and type-filter semantics remain undocumented.
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 names a specific verb and resource: 'Track US federal rules and proposed rules from the Federal Register' by 'term/agency/significance.' This clearly separates it from the SEC-focused siblings like sec_company and sec_events, and the title reinforces the Federal Register scope.
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?
The description gives clear context for when to use this tool: to track federal rules and proposed rules from the Federal Register. It does not explicitly name sibling alternatives or exclusions, but the purpose is specific enough that an agent can infer its use case without confusion.
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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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.