Look up US federal agencies and their slugs (used to filter the other tools by issuing agency). Optionally pass a query to match by name, e.g. 'environmental' or 'defense'.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Filter agencies whose name contains this text. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. It states the tool returns agencies and slugs but does not mention pagination, error cases, or side effects. Adequate for a simple lookup but could be more transparent.
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?
Two sentences, no fluff. Every word adds value. Front-loaded with the key purpose.
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?
For a simple 1-parameter tool with no output schema, the description covers the essential: what it returns, how to filter, and why to use it (slugs for sibling tools). Lacks return format details but acceptable.
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 already describes the query parameter (100% coverage). Description adds optionality and examples, which help the agent understand usage beyond schema constraints.
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?
Clearly states the verb ('look up'), resource ('US federal agencies'), and the purpose of the result ('slugs used to filter other tools'). The tool is distinct from siblings which deal with documents and orders.
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?
Explains that the slugs are used to filter other tools and that a query can be passed to filter by name. Provides example queries. Does not explicitly state when not to use, but the context is clear.
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.
Each tool targets a distinct workflow: agency lookup, document detail, EO search, recent-document monitoring, and general search. There is minor overlap between recent_documents and search_documents, but their descriptions make the intended use clear.
All names are lower_snake and resource-oriented, but the pattern is not perfectly uniform: most are nouns (agencies, document, executive_orders, recent_documents) while search_documents uses a verb prefix. This is predictable and readable, with a minor deviation.
Five tools is well-scoped for a Federal Register intelligence server: each tool covers a necessary part of the workflow without redundancy or bloat.
The server covers the core regulatory-intel loop: agency discovery, search, recent monitoring, and detailed document retrieval. Minor gaps such as dedicated full-text or docket-level tools exist, but agents can work around them with the provided links and search options.