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CeylonCharts - Colombo Stocks Exchange (CSE) data for AI Agents

Search Colombo Stock Exchange symbols

get_symbols
Read-onlyIdempotent

List available CSE symbols with metadata. Optionally search by company name and/or sector. Returns CSV (symbol,name,sector,industry,is_active,last_updated).

Input Schema

NameRequiredDescriptionDefault
queryNoSearch term to filter companies by name, e.g. "bank" or "trust".
sectorNoSearch term to filter companies by sector, e.g. "bank" or "materials". Matches as a substring, not exact, since source sector names vary in formatting.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / query / description
      Previous value: -"Optional search term to filter companies by name, e.g. \"bank\" or \"trust\"."New value: +"Search term to filter companies by name, e.g. \"bank\" or \"trust\"."
    • changedInput schema / properties / sector / description
      Previous value: -"Optional search term to filter companies by sector, e.g. \"bank\" or \"materials\". Matches as a substring, not exact, since source sector names vary in formatting."New value: +"Search term to filter companies by sector, e.g. \"bank\" or \"materials\". Matches as a substring, not exact, since source sector names vary in formatting."
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds little beyond that profile — it implies a full enumeration when no filters are given but does not state whether results are paginated or capped.

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?

Three short sentences, front-loaded with the core purpose, then the optional filters, then the return shape. No filler or repetition.

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 usefully enumerates the CSV columns (symbol,name,sector,industry,is_active,last_updated), which is the key missing structured information. Minor gaps remain around result size or completeness guarantees, but the definition is sufficient to invoke correctly.

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 both parameters are documented there with examples and substring-match behavior, so the schema carries the load. The description only adds that both filters are optional, which is the baseline expectation.

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 ('List') and resource ('available CSE symbols with metadata'), plus the return format. It is clearly the symbol-universe tool and not confusable with quote/chart siblings, though it never explicitly differentiates itself from the closer-sounding screen_stocks or screen_indices.

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?

'Optionally search by company name and/or sector' implies the filtering use case, which is adequate context. There is no explicit when-to-use/when-not guidance and no mention of alternative tools (e.g., screen_stocks) for broader screening.

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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