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Cyberweasel777

botindex-mcp-server

botindex_zora_intel

Analyze Zora NFT market intelligence with AI-powered risk scores, fair value estimates, creator grades, and trading signals to inform investment decisions.

Instructions

AI-powered Zora market intelligence. Risk scores, fair value estimates, creator grades, BUY/WATCH/FADE signals. $0.05

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions a cost ('$0.05'), which is useful behavioral context about pricing. However, it lacks other critical details like whether this is a read-only operation, if it requires authentication, rate limits, or what format the intelligence comes in (e.g., report, API response).

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

Conciseness4/5

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

The description is concise and front-loaded, stating the core purpose and key outputs in one sentence, followed by pricing. Every element adds value without redundancy. It could be slightly more structured by explicitly separating features from cost.

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

Completeness3/5

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

Given no annotations, no output schema, and 0 parameters, the description provides basic purpose and cost. However, for a tool offering 'market intelligence', it lacks details on output format, data freshness, or scope (e.g., timeframes, asset types). This leaves gaps in understanding what the tool actually returns.

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 input schema has 0 parameters with 100% coverage, so no parameters need documentation. The description appropriately doesn't discuss parameters, which is efficient. Baseline is 4 for 0 parameters as it doesn't need to compensate for gaps.

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 provides 'AI-powered Zora market intelligence' with specific outputs like risk scores, fair value estimates, creator grades, and BUY/WATCH/FADE signals. It distinguishes itself from siblings like 'botindex_zora_creator_scores' by offering broader intelligence rather than just creator scores. However, it doesn't specify the exact verb (e.g., 'retrieve' or 'generate') for the action.

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. With many sibling tools focused on Zora (e.g., 'botindex_zora_attention_momentum', 'botindex_zora_creator_scores'), there's no indication of how this tool's 'market intelligence' differs in context or when one should be preferred over another.

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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