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Search Symbol

search_symbol
Read-onlyIdempotent

Search for stock ticker symbols by company name or keyword. Returns matching symbols with descriptions. Example: search_symbol({ query: "apple" })

Input Schema

NameRequiredDescriptionDefault
queryYesSearch query — company name or keyword, e.g. "apple", "tesla"
_apiKeyYesFinnhub API key

Output Schema

NameRequiredDescriptionDefault
countYesNumber of matching results
resultsYesList of matching symbols

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
      -  {
      -    "_apiKey": "your-finnhub-api-key",
      -    "query": "apple"
      -  },
      -  {
      -    "_apiKey": "your-finnhub-api-key",
      -    "query": "tesla"
      -  }
      -]New value: +[
      +  {
      +    "query": "apple"
      +  },
      +  {
      +    "query": "tesla"
      +  }
      +]
  2. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is fully covered by structured data. The description adds only that results include descriptions, and omits anything about result limits, ranking, or empty-result behavior — useful but thin given the low bar set by annotations.

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?

Two short, front-loaded sentences with zero padding. The inline example is slightly wasteful since the schema already supplies identical examples ({query: "apple"}), making it redundant rather than harmful.

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?

No output schema details need explaining (an output schema exists), annotations cover safety, and the schema fully documents both parameters, so the description is nearly complete for a simple two-param lookup. The only meaningful gap is sibling differentiation, which is a purpose/usage concern rather than a completeness one.

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%, and the schema documents both query and _apiKey, so the baseline is 3. The description restates 'company name or keyword' without adding matching syntax, fuzzy-match behavior, or ticker-vs-name expectations beyond what the schema already says.

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?

States a specific verb and resource (search for stock ticker symbols) plus what it returns (matching symbols with descriptions). It is clear in isolation, though it never distinguishes itself from plausible siblings like resolve_entity or company_register_search, leaving the agent to infer which search surface applies.

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 example invocation implies the intended usage pattern, but there is no explicit when-to-use guidance and no mention of alternatives such as resolve_entity or company_register_search, which an agent would need to choose correctly among ~45 siblings.

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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