get_price_history

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

With no annotations provided, the description carries full burden. It discloses key behavioral traits: two distinct response modes with different outputs (digest vs raw data), what each mode includes (OCHLCV samples, technical indicators, risk metrics for digest mode), and format expectations (yyyy-mm-dd for date mode). However, it doesn't mention rate limits, authentication needs, error conditions, or data freshness.

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 appropriately sized but could be more front-loaded. The first sentence states the purpose, but the detailed mode explanations follow. Some sentences could be tightened (e.g., 'There're two kinds of response mode:' could be 'Two response modes:'). Overall efficient but not perfectly 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?

For a 4-parameter tool with no annotations and no output schema, the description provides good context about modes and outputs but leaves gaps. It explains what the tool returns in each mode but doesn't describe the structure of the 'digest' or 'raw OCHLCV data.' Given the complexity of financial data analysis, more detail about output formats would be helpful.

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 0% schema description coverage, the description compensates well by explaining the semantic relationship between parameters: two distinct modes (period mode vs start_date/end_date mode), format requirements for dates (yyyy-mm-dd), and practical guidance (get at least 3 months for period mode). It clarifies that ticker is required and how period/enum values relate to the 'period mode'.

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 'gets historical price data digest for specified period' with specific mention of response modes. It distinguishes from siblings like get_ticker_data or get_earnings_history by focusing specifically on price history with digest/raw data outputs. However, it doesn't explicitly contrast with all possible siblings.

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 provides clear guidance on when to use each mode: 'period mode' for LLM consumption with digest (recommending 3+ months) and 'start_date/end_date mode' for raw data of specific short date ranges. It doesn't explicitly mention when NOT to use this tool versus alternatives like get_ticker_data or analyze_fng_trend.

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