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

With no annotations, the description carries the full burden and does well: it discloses update cadence ('Updated daily'), response format (JSON), and cost ('Costs 1 credit per call') — an economically important trait rarely stated. It omits auth/subscription requirements and rate-limit behavior, so it's strong but not complete.

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?

It is front-loaded with the returned fields, then sources, then filtering, then cadence/cost/format — a logical progression. It runs somewhat long because the five source descriptions are duplicated from the schema, which is redundant but not wasteful enough to hurt readability.

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?

Despite the absence of annotations and an output schema, the description compensates by enumerating return fields, format, cadence, and cost, which is what an agent needs to decide and call. The main residual gap is permissions/authorization context, which is not addressed.

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 100% and the single enum parameter is fully documented there, so the baseline is 3. The description essentially restates the same source labels and meanings verbatim rather than adding syntax, defaults, or combination rules beyond what the schema already provides.

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 opens with a specific verb and resource ('Returns today's AI-generated market data points for equities') and enumerates the returned fields, so the tool's function is unmistakable. The 'for equities' scope implicitly separates it from get_commodity_signals, but no sibling is named explicitly, so it falls short of the top tier.

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?

It explains how to use the source filter ('Filter by source or omit to receive all data points combined'), which is genuine usage guidance. However, it never states when to prefer this tool over get_stock_analysis, get_commodity_signals, or get_sector_radar, leaving the selection decision to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.