patterns

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

Going well beyond the annotations, the description explains a subtle behavioral trait: same candle shapes can be different patterns depending on prior trend. It also clarifies that `confidence` measures textbook proportionality, not probability or predictive success, and warns it is not backtested. This is valuable behavioral context that the schema and annotations do not convey.

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 dense but well-structured: a clear one-line summary is followed by the most important interpretive caveat, then the confidence semantics. Every sentence earns its place, and the most actionable guidance is front-loaded.

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?

Given 8 parameters, no output schema, and a nuanced detection model, the description covers the key decisions an agent needs: what patterns are, how context affects them, what confidence means, and where to go for predictive analysis. It does not describe the full output shape or enumerate the 16 pattern IDs, which would make it fully complete.

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 coverage is high at 75%, and the description adds meaningful semantics for `ignore_context` by explaining that it shows raw shapes regardless of prior trend. It also clarifies what `confidence` means, which relates to `min_confidence`. However, the description does not add detail for the undocumented `to` and `from` date parameters, or explain how `bars` and `since` interact.

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 identifies the tool's function: detecting candlestick patterns on an IDX stock's daily bars, listing 16 classic formations and the prior trend used for interpretation. It differentiates itself from the sibling `backtest` by explicitly stating that pattern confidence is not predictive and that predictive questions should go to `backtest`.

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 gives strong usage context: it explains how prior trend affects pattern meaning, how to override it with `ignore_context`, and explicitly directs users to `backtest` when they care about forward-looking performance. It does not enumerate all alternative sibling tools or state when not to use this tool versus technicals, so it stops short of a 5.

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