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blockchainacademics

@blockchainacademics/mcp

Official

get_team_info

Retrieve verified team backgrounds, including founders, LinkedIn profiles, prior exits, and doxx status for a crypto entity.

Instructions

Founders, LinkedIn-verified backgrounds, prior exits, doxx status. Entity-graph backed. Pro tier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_slugYes
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It states the tool is 'Entity-graph backed' but does not mention whether it is read-only, if it requires authentication, rate limits, or any side effects. This is insufficient for an agent to understand operational invariants.

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

Conciseness3/5

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

The description is short and uses bullet-like phrasing, but it is not structured to front-load the most critical information (what the tool does and its input). The sentence 'Entity-graph backed. Pro tier.' adds minimal value and could be integrated more effectively.

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?

Given the low parameter count and lack of output schema or annotations, the description does not provide sufficient context for confident invocation. It omits return format, pagination, error conditions, or examples, leaving the agent with significant uncertainty.

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

Parameters1/5

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

The only parameter 'entity_slug' has no description in the schema (0% coverage) and the tool description does not explain its format or meaning. The description lists outputs but fails to connect the parameter to the data retrieval, leaving the agent without guidance on how to set the parameter.

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 lists specific outputs (Founders, LinkedIn-verified backgrounds, prior exits, doxx status) and mentions the underlying data source (Entity-graph backed), making the tool's purpose clear. However, it does not explicitly state that it provides information for a given entity slug, which would strengthen clarity.

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 its many siblings (e.g., get_entity, get_explainer). It mentions 'Pro tier' implying a cost or access restriction but gives no explicit usage context or alternatives.

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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