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BeevR

About BeevR

about_beevr
Read-onlyIdempotent

Who BeevR is, its AI capabilities (production agents, HIPAA AI, GraphRAG, Kite framework) and how to contact the team.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is fully covered without the description. The description adds that the payload is descriptive company/profile content and includes contact routing, which is modest but real added context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with the subject first and the three content categories packed into one clause. No filler, no restatement of the tool name, nothing that could be cut.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, read-only informational tool with no output schema, the description adequately signals what the agent will get back. It is complete enough to invoke correctly, with only a minor gap in not indicating depth or format of the returned profile.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is no parameter semantics to explain and the baseline of 4 applies. The empty schema matches the description's implication of a parameterless, fetch-everything call.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource (BeevR) and enumerates the content it returns: identity, AI capabilities, and contact info. It distinguishes itself from data-fetching siblings like get_article or get_pricing by being an orientation/about tool, though it never explicitly contrasts itself with them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the content list – an agent can infer this is for general background questions about the vendor and for finding contact channels. However, there is no explicit 'use this when' trigger and no stated alternative or exclusion, so guidance remains inferential.

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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