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Fetch article (ChatGPT connector)

fetch
Read-onlyIdempotent

ChatGPT connector contract: fetch one article by the id returned from search. Returns the enriched digest (summary, per-ticker analysis, category, relevance) — not the full article body — plus the canonical alphai.io URL for citation. When the article has a published SEC earnings read, text also includes its reported metrics with year-over-year and sequential comparisons, segments, guidance, concerns and missing items. Raises not_found for an unknown id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesArticle id from a search result.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
urlYes
textYes
titleYes
metadataNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / id / maxLength
      Added value: +64
  2. Added

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description correctly adds non-obvious behavior: it returns a digest rather than the full body, includes SEC earnings data conditionally, and raises not_found for unknown ids. No contradiction with 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?

The description is information-dense and front-loaded with the core action, followed by return behavior, conditional content, and error handling. The opening phrase 'ChatGPT connector contract' is slightly redundant with the title, but every other clause earns its place.

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 simple one-parameter fetch tool with rich annotations and an output schema, the description covers the input source, the exact return shape, a conditional enrichment behavior, and error semantics. An agent has enough context to invoke the tool correctly without needing to open sibling schemas.

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?

The schema has 100% description coverage for the single id parameter, and the description reinforces the same guidance ('id returned from search') without adding new syntax or format details. Baseline 3 is appropriate because the schema already carries the parameter meaning.

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: 'fetch one article by the id returned from search.' It clearly differentiates itself by saying it returns the enriched digest and 'not the full article body,' which separates it from sibling tools like alphai_article and search.

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?

Provides clear usage context: use after search, with an id returned from search, when you want the enriched digest rather than the full article body. It does not explicitly name an alternative tool for retrieving the full body, so it stops short of full when-to-use vs. alternative guidance.

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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