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antoncoding

BrianKnows MCP Server

by antoncoding

search

Search blockchain and DeFi information across specialized knowledge bases using Brian's knowledge engine to find relevant data and insights.

Instructions

Search using Brian's knowledge engine

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query
kbNoKnowledge box to search in (default: public-knowledge-box). Options: circle_kb, lido_kb, Polygon_kb, taiko_kb, near_kb, clave_kb, starknet_kb, consensys_kb
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. 'Search using Brian's knowledge engine' implies a read-only operation but doesn't specify what kind of results to expect, whether there are rate limits, authentication requirements, or any constraints on the search. The description is too minimal to provide adequate behavioral context for a search tool.

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?

The description is extremely concise with just one sentence containing 5 words. It's front-loaded with the core functionality and wastes no words. This is an appropriate level of conciseness for a simple search tool.

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

Completeness2/5

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

For a search tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what kind of results to expect, the format of returns, whether there are limitations on query complexity, or how results are ranked. The minimal description leaves too many questions unanswered for effective tool selection and invocation.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents both parameters (query and kb) with descriptions and enum values for kb. The description doesn't add any additional meaning beyond what's in the schema - it doesn't explain what 'Brian's knowledge engine' means in relation to the parameters or provide usage examples.

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 clearly states the tool performs a search operation using a specific knowledge engine (Brian's knowledge engine), which provides a specific verb+resource combination. However, it doesn't distinguish this tool from its siblings (agent, ping) since they appear to be unrelated tools rather than alternative search methods.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. There's no mention of when this search tool is appropriate versus other search methods, nor any context about when not to use it. The sibling tools appear unrelated, so no explicit comparison is made.

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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