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entity_read

Look up any entity by symbol, slug, contract/wallet address, operator or vault name.

    Returns {entity_type, id, score, grade, confidence, receipt_hash,
    links}. When nothing resolves returns {match: null, did_you_mean:
    [up to 5 candidates]} rather than an error.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -{
      -  "properties": {
      -    "result": {
      -      "title": "Result",
      -      "type": "string"
      -    }
      -  },
      -  "required": [
      -    "result"
      -  ],
      -  "title": "entity_readOutput",
      -  "type": "object"
      -}New value: +null
  2. Added

TDQS

A4.1/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the return shape ({entity_type, id, score, grade, confidence, receipt_hash, links}) and, crucially, that a miss returns {match: null, did_you_mean: [...]} rather than an error. This is a valuable behavioral trait for an agent to know. It stops short of stating auth needs or rate limits, hence a 4 rather than 5.

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?

Front-loaded with the core action, then the return shape and the miss behavior. Two tight sentences, though the line-broken formatting of the return object is slightly clunky for a prose description. No filler.

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?

With no output schema, the description must describe returns, and it does for both the success and miss paths, including the did_you_mean fallback. For a single-param lookup with no annotations, this is close to complete. It could go further on auth/permissions, but nothing essential is missing.

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?

Schema coverage is 0% for the single 'query' parameter, so the description must compensate, and it does: it enumerates the identifier forms accepted (symbol, slug, contract/wallet address, operator, vault name). That is substantive meaning beyond the bare schema. One param with no enum keeps it at 4 rather than 5.

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?

States a specific verb (look up) and resource (any entity) and enumerates accepted identifier types (symbol, slug, contract/wallet address, operator, vault name). This clearly distinguishes it from siblings like basis_answer and get_stablecoin_scores, which are analytical rather than lookup tools.

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?

The description implies this is a general-purpose resolution tool for any identifier, and the enumeration of identifier types signals when it applies. However, it does not explicitly state when to prefer basis_answer, basis_data, or other siblings, leaving the agent to infer the boundary.

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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