Buffett Quality Score (0-100) over a 5-year window: owner earnings, ROE consistency at 15%, balance-sheet safety, FCF quality. Foreign private issuers (20-F) excluded unless exclude_foreign=False. Not investment advice. Cost: $0.25.
| Name | Required | Description | Default |
|---|---|---|---|
| fy | No | ||
| limit | No | ||
| industry | No | ||
| min_score | No | ||
| min_revenue | No | ||
| exclude_foreign | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the cost ($0.25), states it's not investment advice, and mentions default exclusion of foreign issuers. However, it does not specify whether the tool is read-only, any rate limits, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, concise and front-loaded with the core functionality. The first sentence explains the score and components, the second adds a filter, and the third adds a disclaimer and cost. Minimal waste, though could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters, no annotations, and an output schema, the description lacks completeness. It omits parameter explanations for 5 parameters and does not clarify expected inputs like fiscal year or industry filter. The cost and output schema help but are not sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only explains the 'exclude_foreign' parameter in context. The other five parameters (fy, limit, industry, min_score, min_revenue) are not described, leaving the agent without sufficient meaning for their usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool computes a Buffett Quality Score (0-100) over a 5-year window based on owner earnings, ROE consistency, balance-sheet safety, and FCF quality. It distinguishes itself from siblings like 'buffett_value' and 'screen_companies' by specifying its unique scoring methodology.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide guidance on when to use this tool versus alternatives. It only mentions that foreign private issuers are excluded by default unless 'exclude_foreign=False', but no comparative context or prerequisites are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct purpose: quality scoring, valuation, raw facts, filings, financials, peer comparison, industry aggregates, insider activity, institutional ownership, market insights, screening, short pressure, and standard scores. No overlaps in functionality.
All tools use consistent snake_case naming with descriptive prefixes (e.g., company_, buffett_, market_). The pattern is predictable and helps infer tool purpose.
14 tools cover a broad range of SEC fundamentals without being overwhelming. Each tool serves a clear role, and the count is appropriate for a comprehensive financial data API.
Covers core areas: filings, financials, insider trades, institutional ownership, screening, scores, and market insights. Minor gaps (e.g., no direct analyst estimates or corporate events) but overall very well-scoped for the domain.