federal-regulations-mcp-server

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

Annotations declare readOnlyHint and openWorldHint. The description adds behavioral details: structure walks the hierarchy, search returns snippets and hierarchy paths, and the source is reported. It does not contradict annotations.

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 concise (four sentences) and well-structured, front-loading the purpose. Every sentence provides essential information without 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?

Given the tool's complexity (two modes, multiple parameters) and the presence of a full input schema and output schema, the description covers the main behavioral aspects. It might lack detail on error handling or pagination in structure mode, but overall it is sufficiently complete for an agent to use effectively.

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 coverage is 100%, so baseline is 3. The description adds meaningful context: explains how 'date' affects historical hierarchy and point-in-time search, mode values are elaborated, and per_page is clarified as search-only. This adds value beyond the schema.

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 tool explores the eCFR via two modes (structure and search). Distinguishes from siblings by specifying it feeds into regulations_get_cfr_section and is used when the exact citation is unknown.

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 explains when to use each mode: structure for discovering unknown citations, search for full-text queries. It also connects to a sibling tool for detailed section retrieval. However, it does not explicitly list when not to use this tool versus alternatives like regulations_search_rules.

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

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

Annotations already declare readOnlyHint and openWorldHint. The description adds value by disclosing that the list endpoint returns no body text or attachment info, that call comment_id to read body, that attachments with stub body have attachmentOnly=true, and that API key is required. This goes well beyond the annotations' minimal safety profile.

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 well-structured, front-loading the purpose and then explaining parameters and behaviors. Every sentence adds value, though it is slightly long due to the need to cover four parameter modes. Slightly verbose but not wasteful; a clear 4.

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?

Given the tool's complexity (4 parameter modes, pagination, attachment handling, API key requirement), the description covers all essential aspects: what the tool retrieves, the distinct behaviors of list vs. detail endpoints, attachment handling, and prerequisite (API key). With an output schema present (not shown but referenced as 'has output schema: true'), the description is complete.

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 100%, so baseline is 3. The description adds usage context beyond schema: e.g., labeling docket_id as 'broadest scope', comment_id as 'use to read a single comment's body', and explaining fr_document_number as a convenience that saves hops. This additional layer of guidance merits a 4.

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 states 'Fetch public comments' and details the four distinct targeting parameters (docket_id, document_object_id, fr_document_number, comment_id), specifying the resource and scope. It distinguishes this tool from siblings by focusing exclusively on comments, and the phrase 'unique corpus of what citizens and organizations actually submitted' adds specific purpose context.

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 explicitly instructs 'Provide exactly one targeting parameter' and explains when to use each: docket_id for broadest scope, document_object_id for one document, fr_document_number as convenience, comment_id to read a comment's body. It also notes limitations (20-page cap, sample for high-volume dockets) and suggests narrowing via document_object_id, providing clear when-to and when-not-to guidance.

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

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

Annotations provide readOnlyHint and idempotentHint; description adds that it uses eCFR, retains historical versions, and that early dates are rejected with guidance. No contradictions.

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?

Every sentence is purposeful, no filler. Front-loaded with purpose, then usage guidelines, then parameter hints. Appropriate length for the tool's complexity.

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?

Given output schema exists, description doesn't need to detail return format. It covers versioning, performance (local mirror), error cases (date rejection), and usage patterns. Complete for a read-only, idempotent 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 descriptions cover all 4 parameters (100%), but the description adds guidance on combining title, part, and section, and clarifies the behavior of omitting section. This adds meaning beyond schema.

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 states it reads CFR section/part text, current or historical, and distinguishes from siblings like regulations_browse_cfr (for browsing structure) and regulations_search_rules (for searching).

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?

Describes when to use (e.g., answering 'what does 40 CFR 50.1 say today'), when to omit section (fetch whole part with length warning), and date constraints (coverage since ~2017, rejection before). Also mentions local mirror for current reads and source reporting.

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

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

Annotations already declare readOnlyHint and idempotentHint true. The description adds valuable context beyond annotations: requires API key, pagination limits (20 pages, 5,000 records), and that dockets often contain hundreds of supporting materials.

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?

Four concise sentences, each carrying essential information. Front-loaded with purpose, then usage guidance, and finally prerequisite. No redundant or unnecessary text.

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?

Given the tool's complexity (4 parameters, output schema exists), the description is complete. It explains the docket concept, return contents, filtering strategies, and even provides a real-world example docket ID.

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 coverage is 100% but description adds significant meaning: explains docket_id format, clarifies that document_types filter helps find rule documents, and mentions pagination behavior. This goes beyond schema descriptions.

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 states it pulls a rulemaking docket by docket ID, including metadata and documents. It specifies the exact resource (docket) and action (pull), and distinguishes from siblings like regulations_find_comments and Federal Register tools.

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 provides clear context for when to use the tool (to get a docket's metadata and documents) and prerequisites (requires API key). It also offers guidance on filtering document types to find rule documents, but does not explicitly exclude alternatives.

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

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

Annotations already provide readOnlyHint and idempotentHint. The description adds value by noting that full text can be large (final rules tens of thousands of words) and that the output carries cross-source handles and chaining info. No contradiction with annotations.

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, front-loaded with primary purpose, then details. Each sentence earns its place. Could be slightly more concise but overall efficient.

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?

Given an output schema exists, the description need not explain return values. It explains cross-links, chaining, and large-text warning, which is sufficient for a simple fetch-by-id tool. No gaps identified.

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 coverage is 100%, and the description adds meaningful usage guidance: document_number's format and source, and include_full_text's trade-off. This goes beyond the schema descriptions.

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 states it fetches a single Federal Register document by FR document number, listing full metadata and cross-source handles. It distinguishes from siblings like regulations_search_rules (which returns multiple) and regulations_get_docket (which gets a docket). The verb 'fetch' and resource 'Federal Register document' are specific.

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 advises when to set include_full_text (only when rule body is needed), and explicitly chains to other tools (regulations_get_docket, regulations_find_comments, regulations_get_cfr_section). However, it does not explicitly state when to not use this tool in favor of siblings, though the context of sibling names helps infer.

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

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

The description adds significant behavioral context beyond annotations: it is fully functional without a key, enriches rows with comment count when the key is set, and advises using sibling tools for more details. No contradictions with readOnlyHint and openWorldHint.

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 sentences, front-loaded with the main purpose, and every sentence provides essential information without 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?

With an output schema present, return format explanation is unnecessary. The description covers use cases, behavior, parameter nuances, and integration with sibling tools, making it fully informative for agent selection.

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?

Input schema covers 100% of parameters with clear descriptions. The description adds value by noting the sort order and page limit implications, but the schema already does the heavy lifting, so baseline 3 is appropriate.

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 explicitly states the tool lists rules open for public comment, with filtering and sorting by closing date. It clearly identifies the resource and action, distinguishing it from siblings like regulations_search_rules and regulations_get_document.

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 provides a use case ('What can I still weigh in on?'), mentions the data source (Federal Register), and explains behavior with/without an API key. It references sibling tools for next steps, but lacks explicit 'when not to use' guidance.

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

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

Discloses pagination limits (50 pages, 10,000 results) and suggests workarounds. Annotations confirm read-only (readOnlyHint=true), and 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?

Well-structured with front-loaded purpose. Slightly long but every sentence conveys essential information without 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?

Given output schema exists, description explains result context (document number, docket IDs, RINs, affected CFR parts) and links to other tools. Comprehensive for a search tool with good annotations.

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 coverage is 100%, yet the description adds significant value by explaining page limits, per_page max, and the meaning of type enum values. Provides usage guidance for each parameter beyond the schema.

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 states the tool searches the Federal Register with specific filters and identifies it as the primary discovery entry point, distinguishing it from sibling tools like regulations_get_document.

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 advises when to use (primary discovery) and how to narrow results (use date filters, not deeper paging). Notes that results chain into other tools. Could add explicit when-not scenarios, but sufficient context is provided.

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