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gold-silver-analytics

by io.github.Gren70
OverviewDiscussionsAdmin

Search tickers by name or symbol

search_tickers
Read-only

Fuzzy lookup: returns free-subset rows whose ticker symbol or company name contains the query (case-insensitive). For structured filter/rank, use get_screen_data instead.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search_tickers"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesSubstring to match against ticker symbol or company name.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, and the description adds behavioral details beyond those: case-insensitive substring matching and returning rows that contain the query. The phrase 'free-subset rows' is somewhat vague but does not contradict annotations.

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?

Two concise sentences, front-loaded with the primary action and followed by a useful alternative reference. No wasted words.

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?

For a single-parameter search tool with read-only annotations and no output schema, the description covers the core behavior and provides an alternative. The 'free-subset' phrase introduces minor ambiguity but does not undermine overall completeness.

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 coverage is 100%; the only parameter 'query' is fully described in the schema. The description does not add meaning beyond the schema, so the baseline 3 applies.

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 uses a specific verb ('lookup') and resource ('tickers'), clearly stating it matches by symbol or company name via fuzzy substring. It also explicitly distinguishes itself from get_screen_data, making its purpose unambiguous.

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 indicates a use case (fuzzy lookup) and explicitly recommends an alternative (get_screen_data) for structured filter/rank. However, it does not contrast with list_tickers, leaving a slight ambiguity for when to use each sibling.

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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