get_memberRetrieve detailed information about a specific U.S. member of Congress by their Bioguide ID (e.g., "P000197" for Nancy Pelosi).
| Name | Required | Description | Default |
|---|---|---|---|
| bioguide_id | Yes | Bioguide ID (e.g., "P000197") |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotation readOnlyHint=true already covers the safety profile, and the description's 'Retrieve' is consistent. The description adds little beyond the lookup condition (e.g., no mention of not-found behavior or return format), but the annotation lowers the burden, so a mid-range score is appropriate.
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 containing the verb, resource, method, and an example, with no wasted words. It fully informs in 18 words.
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 that this is a simple lookup with one parameter and no output schema, the description is largely complete: it explains what the tool does, how to invoke it, and gives an example. It does not detail the fields of the returned information, but 'detailed information' is a reasonable summary for this low-complexity 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 coverage is 100%, with the parameter description already giving the example 'P000197'. The tool description repeats that example and adds 'U.S. member of Congress' context, but this does not add significant meaning beyond what the schema already provides, hence the baseline score of 3.
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 states a specific verb ('Retrieve'), resource ('detailed information about a specific U.S. member of Congress'), and method ('by their Bioguide ID'). It distinguishes itself from siblings like search_members (search) and get_member_vote (vote details), making the purpose unambiguous.
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 clearly implies when to use the tool: when you have a Bioguide ID and need member details. However, it does not explicitly mention when not to use it or direct users to alternatives like search_members when the ID is unknown, so it lacks explicit exclusion/alternative guidance.
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 resource or action: efforts, members, policies, stories, representatives, voter info, and text retrieval. Even similar tools like get_effort and resolve_effort clearly differ in input type (ID vs natural language), and get_stories vs get_story follow the standard list/detail distinction.
All tool names follow a consistent verb_noun pattern using lower_snake_case: get_ for retrieval, search_ for queries, and resolve_ for name resolution. Nouns are clear and descriptive, with no mixing of styles or inconsistent verbs.
With 12 tools, the set is well-scoped for a U.S. political policy tracking service. Each tool provides a distinct utility without overwhelming the surface, fitting solidly within the expected range.
The tool surface covers the core read-only workflows: searching and retrieving policies and members, resolving and retrieving efforts, listing and retrieving story bundles, and looking up representatives and voter info. There are no obvious gaps or dead ends for the stated purpose.