candlestick_patterns

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds valuable context by explaining that each hit reports the trend it appeared in and whether it is a genuine reversal, with a concrete example of a hammer in an uptrend. This goes beyond basic functionality and informs the user about the tool's interpretive behavior, which is a significant transparency bonus.

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 compact and well-structured, with an introductory sentence, an Args section explaining each parameter, and a final note adding important context. Every sentence contributes value without redundant fluff. The formatting is clean and scannable.

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?

An output schema exists to handle return values, so the description is relieved from explaining outputs. The description covers the core purpose, all parameters, and a key interpretive nuance (trend context). Missing elements include potential limitations (e.g., which pattern types are supported) and behavior when no patterns are found, but overall it is sufficiently complete for a single-purpose detection tool.

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 0%, so the description must compensate. It does so by providing plain-language definitions for all four parameters: symbol ('Ticker'), market (with explicit allowed values 'crypto', 'stock', or 'idx'), interval ('Candle size'), and lookback (with a range '1-20'). While 'interval: Candle size' is somewhat vague, it still provides meaning beyond the raw schema, making the tool more usable.

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's purpose: 'Detect candlestick patterns in the most recent bars.' The verb 'detect' is specific, and the resource 'candlestick patterns' is narrowly defined, distinguishing it from broader tools like technical_analysis or multi_timeframe_analysis. The scope ('most recent bars') adds further specificity.

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 implies usage for detecting candlestick patterns but does not explicitly state when to use this tool versus alternatives. There is no mention of when not to use it or comparison with sibling tools like technical_analysis or market_snapshot. The note about trend context provides some guidance on interpretation, but no explicit exclusions or alternatives.

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