screen_stocks

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

With no annotations, the description provides useful behavioral context: it discloses data-dependent coverage, names specific free-data sources, and flags the V1 limitation. It doesn't mention side effects, auth, or rate limits, but the read-only nature is implied by 'analyze/rank'.

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 and front-loads the main action. The internal method reference ``_enhance_snapshot_with_free_data`` is implementation noise that could be dropped without losing functional guidance, preventing a perfect score.

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?

The output schema covers return values, and the description covers purpose, data dependencies, and a key alternative. However, the min_score parameter is entirely undocumented, so an agent cannot fully utilize the tool's filtering capabilities. It's suitable for basic invocation but not for confident parameter-driven use.

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?

The input schema has zero descriptions for both parameters. The description only indirectly explains tickers as a 'ticker universe' or 'ticker list', and it never mentions min_score at all. An agent cannot understand how to use min_score or what filtering it applies.

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 states a specific verb ('analyze and rank') and resource ('explicit ticker universe'), and explicitly differentiates from discover_stocks by noting that V1 requires a ticker list rather than scraping the whole market. It also clarifies that every ticker is scored, with data-driven caveats.

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 explicitly points to discover_stocks as the alternative when market-wide scraping is desired, and communicates that this tool is for a pre-specified ticker universe. This gives a clear when-to-use versus when-not-to-use distinction, though it doesn't mention other siblings like analyze_stock.

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