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callbk

finlight-mcp

get_article_by_link

Retrieve financial news article details by URL, including sentiment analysis and optional full content. Get title, summary, date, source, and tagged company entities.

Instructions

Retrieve a specific financial news article by its URL from the Finlight database.

Use this when you have an article URL and want to get its full details including:

  • Title, summary, and publication date

  • Source domain and language

  • Sentiment analysis (positive/negative/neutral) with confidence score

  • Optionally: full article content and tagged company entities

This is useful for getting details about a specific article you found elsewhere or for enriching article data with sentiment and entity information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
linkYesThe full URL of the article to retrieve. Example: "https://www.reuters.com/technology/nvidia-reports-record-revenue-2024"
includeContentNoInclude the full article text content. Requires a subscription plan with content access. Default: false
includeEntitiesNoInclude tagged company entities with ticker symbols, exchange info, sector/industry classification, ISIN codes, and OpenFIGI identifiers. Requires subscription. Default: false
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It lists the returned data (title, summary, date, source, language, sentiment, optional content/entities), which gives a solid picture of behavior. It does not mention error cases or rate limits, but for a simple retrieval tool, this is acceptable.

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 well-structured with a clear purpose statement, a usage context paragraph, and a bulleted list of return fields. There is slight redundancy between 'Use this when' and 'This is useful for', but overall it is efficient and readable.

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 3-parameter tool with full schema coverage and no output schema, the description explains the purpose, use case, and expected return fields well. It could mention subscription requirements in the body (covered in schema), but it is otherwise complete.

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%, with detailed descriptions for link, includeContent, and includeEntities. The description's mention of optional content/entities adds little beyond the schema, so it meets the high-coverage baseline.

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 opens with 'Retrieve a specific financial news article by its URL from the Finlight database,' which clearly identifies the verb and resource. It distinguishes from siblings by specifying 'Use this when you have an article URL,' implying search_articles/list_sources are for different needs.

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 provides explicit when-to-use guidance: 'Use this when you have an article URL' and 'This is useful for getting details about a specific article you found elsewhere.' It does not explicitly name the alternative tools or give a when-not-to-use scenario, but the context is clear.

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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