quality_stock_review

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

With no annotations provided, the description carries the full burden and does disclose meaningful behavior: which databases are read, how the 5-day return is computed, and the research-only disclaimer. However, it does not clarify whether the tool is strictly read-only or whether '给出反思建议' writes reflections back to a database, nor does it mention auth needs or failure behavior when no pushes exist in the window.

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 opens with a front-loaded purpose statement, follows with a two-part methodology sentence, and closes with a necessary legal disclaimer. Every sentence earns its place and there is no fluff, though the two-paragraph layout is slightly more verbose than strictly necessary.

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 moderate complexity (joining two databases, computing returns, aggregating stats, generating reflections), the description covers inputs, processing steps, and caveats. Since an output schema exists, return values need not be described. Minor gaps remain around edge cases (no data in window) and write behavior, but an agent has enough to invoke it correctly.

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% — the single 'days' parameter is documented in the schema with its default and meaning (backtest lookback window of 20 days). The description itself adds no parameter-level detail, so the baseline 3 applies; no compensation needed since the schema fully covers semantics.

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 and resource: it tracks the 5-day win rate of historical 'quality stock' pushes, explicitly citing the data sources (reports.db with rtype='qualitystock', market_data.db closing prices) and the exact computation (5-trading-day returns, aggregated win rate and average return). It is clearly distinct from siblings like report_history or backtest_strategy because it evaluates the performance of the tool's own past recommendations, though it does not explicitly name a differentiating sibling.

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?

Usage context is implied: an agent can infer this tool is for evaluating past quality-stock recommendation performance, especially alongside backtest_strategy or trading_suggest. However, there is no explicit when-to-use vs. when-not-to-use guidance, no named alternatives, and no exclusion conditions, so routing among the large sibling set is left to inference.

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