stock_a_ttm_lyr

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

Annotations (readOnlyHint, idempotentHint, destructiveHint) already declare a safe read operation. The description adds only the return type (DataFrame) and data content, but no additional behavioral context such as data frequency, coverage, or potential side effects. With annotations present, this is an average contribution.

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 extremely short but redundant, essentially repeating the title twice and adding only the return type. It is under-specified rather than concise, with no additional value beyond the structured title.

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?

For a simple no-parameter data retrieval tool with no output schema, the description adequately names the two data fields and return type. However, it lacks context on data frequency, universe definition, and source, making it slightly less complete than ideal.

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?

With zero parameters, the schema fully covers all inputs. The description has nothing to add about parameter behavior, and the baseline for zero-parameter tools is 4. It correctly communicates no inputs are required.

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 the tool provides equal-weighted and median PE ratios for all A-shares. The verb is implied ('get'/'fetch') and the resource specificity is good, but it doesn't distinguish itself from sibling tools like stock_index_pe_lg or stock_market_pe_lg.

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?

No guidance is provided on when to use this tool versus alternatives. It does not mention exclusions or preferred contexts, leaving the agent without criteria for selection among the many PE-related sibling tools.

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