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AlphAI

by io.github.makeev
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List supported tickers

alphai_tickers
Read-onlyIdempotent

List supported tickers (US stocks/ETFs, crypto, and foreign listings). Optionally filter by query (prefix on ticker, substring on name, or the company's brand name where that differs from its registered one — q='spacex' finds SPCX, registered as SPACE EXPLORATION TECHNOLOGIES CORP) or by sector. currency is the trading currency (USD for US listings and crypto pairs, the local currency for foreign ones); country is the ISO alpha-2 country of domicile and is null for crypto, which has no jurisdiction of incorporation. Also answers 'when does X next report': next_report_date is the date of the next earnings report the source marks as confirmed, in America/New_York; a company can still move it. It is NEVER an estimate — null means AlphAI holds no confirmed date, which is not the same as the company not reporting. A confirmed date typically surfaces about five weeks ahead, so a null this far out is normal. When the report lands, alphai_earnings(ticker) returns AlphAI's read of it.

Input Schema

NameRequiredDescriptionDefault
qNoTicker-prefix matches first, then company-name substring matches.
limitNoMax rows to return.
offsetNoPagination offset.
sectorNoFilter by sector (case-insensitive).

Output Schema

NameRequiredDescriptionDefault
itemsNo
totalYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / q / anyOf
      Previous value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "maxLength": 64,
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
    • changedInput schema / properties / sector / anyOf
      Previous value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "maxLength": 64,
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
  2. Changed1 schema field changed
    • addedOutput schema / properties / items / items / properties / next_report_date
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null
+}
  3. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already cover readOnly/idempotent/non-destructive, and the description adds genuinely new behavioral context: currency conventions per listing type, country being null for crypto because there is no jurisdiction of incorporation, and a careful explanation of next_report_date (confirmed-only, never an estimate, null ≠ no report, ~5 weeks lead time, company may move it). That is exactly the kind of caveat an agent needs to avoid misreporting.

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?

Purpose and coverage are front-loaded, then filtering semantics, then the next_report_date caveat. Every clause carries information an agent would otherwise have to guess; the SPCX example is the only slightly indulgent flourish, and it is justified by illustrating non-obvious alias matching.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a four-param, read-only listing tool with a full output schema, this covers everything needed: what universe it spans, how q and sector behave, and how to interpret the fields most likely to be misread (currency, country, next_report_date). Nothing material is left for the agent to infer.

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 100%, so the baseline is 3; the description earns above that by explaining that q also matches a company's brand name when it differs from the registered name, with a concrete SPCX/'spacex' example that the schema does not convey. The sector parameter gets no added meaning beyond the schema's case-insensitive note.

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 and resource ('List supported tickers') and immediately scopes coverage to 'US stocks/ETFs, crypto, and foreign listings'. It also names a downstream sibling ('alphai_earnings(ticker)'), so an agent knows this is the universe/discovery tool rather than a news or analysis tool.

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?

Gives concrete usage contexts: resolving a company or brand name to a ticker via q, filtering by sector, and answering 'when does X next report'. However, it never names an alternative tool (e.g. search, fetch) or states when NOT to use it, so routing guidance is implied rather than explicit.

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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