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romaco-labs

@romaco/mcp

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by romaco-labs

romaco_draw_pattern

Visualize detected chart patterns by drawing their geometry (necklines, trendlines, targets) directly on your chart. Uses deterministic math from candle data, never altering user drawings.

Instructions

Draw the GEOMETRY of a detected chart pattern on the user's browser chart: head & shoulders neckline + silhouette, double top/bottom extremes + trigger line, triangle border trendlines, flag polyline — plus faint dotted target/invalidation levels when the pattern projects them. Patterns are re-detected from the loaded candles (deterministic math, never agent-supplied geometry) and only RECENT patterns qualify — if none match, nothing is drawn and that is the honest answer. Each pattern family owns one drawing group, so re-drawing a family replaces it atomically and the user's own drawings are never touched. Offer this after romaco_detect_patterns or romaco_thesis finds something; call it ONLY after the user accepts. Requires mounted and candles loaded (romaco_load_candles), with the SAME symbol/range on the chart.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoPattern kind to draw. Omit to draw the highest-confidence recent pattern of any kind.
rankNo0-based confidence rank among matching recent patterns (0 = strongest). Default 0.
Behavior5/5

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

Despite no annotations, the description discloses key behaviors: patterns are re-detected deterministically, only recent patterns qualify, drawing groups are atomic and user drawings untouched, prerequisites (mounted MCP bridge and loaded candles), and honest answer if no match.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is comprehensive but slightly lengthy. However, every sentence adds value and it is clearly structured with front-loaded main action, details, and usage conditions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and the complexity of the tool, the description covers prerequisites, behavior under no match, drawing group management, and specific pattern elements drawn. It leaves no major gaps for an AI agent to understand invocation and outcome.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers 100% of parameters, but description adds meaning: explains that omitting 'kind' draws highest-confidence recent pattern, clarifies 'rank' as 0-based confidence index, and introduces the concept of 'recent patterns'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifies the exact action (draw geometry of detected chart pattern), enumerates pattern families and what is drawn for each, and distinguishes from sibling tools like romaco_add_drawing by stating it is for detected patterns after user acceptance.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use: after romaco_detect_patterns or romaco_thesis finds something, and only after the user accepts. Indicates when not to use (if no pattern detected, nothing is drawn) and implies alternatives exist for manual drawing.

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

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