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find_expert

Rank likely Celestia experts on a topic across blobpedia: forum activity matching the topic, plus overall forum volume of that author. Celestia-specific.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax authors (default 5).
topicYesTopic / domain to find experts for.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It does explain that ranking is based on forum activity matching the topic plus overall author volume, which is useful. However, it doesn't mention output format, potential empty results, or any limitations of the ranking heuristic.

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 two sentences with zero filler. The primary action and resource are front-loaded, and the ranking criteria are stated compactly. Every word adds value.

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?

For a two-parameter tool, the description is mostly complete for invoking it: topic name and optional limit are clear. But because there is no output schema, the description should explain what the ranked result looks like (e.g., author names, scores, counts); it doesn't. This is a notable gap, though not critical for basic 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 (limit and topic). The description adds no new parameter-specific details beyond restating that the topic drives forum matching, which is already implied by the parameter name and schema description.

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

Purpose5/5

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

The description states a specific verb ('Rank') and a specific resource ('likely Celestia experts on a topic across blobpedia'). It also reveals the ranking methodology (forum activity matching the topic plus overall forum volume), which makes its purpose distinct from sibling tools like search, find_similar_projects, or find_maintainer_guidance.

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

Usage Guidelines4/5

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

The description clearly establishes when to use this tool: when the user wants to identify experts on a topic within the Celestia ecosystem via blobpedia forum activity. It doesn't explicitly name alternatives or exclusion conditions, but the domain-specific phrasing ('Celestia-specific') and expert-ranking focus provide enough contextual signal to route an agent.

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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