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inksmcp

by bhanutpt
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Python
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plot

Draw labeled data series on an existing grid using DATA values, avoiding coordinate math. Add lines, markers, and point labels for diagrams and annotations.

Instructions

Plot data on a grid made with the grid tool, in DATA values — no coordinate maths. grid: that grid's id_prefix. Each series: {"points": [[x, y], ...], "line": true, "stroke": "#1f77b4", "stroke_width", "stroke_dasharray", "marker": "circle"|"square"|"diamond"|"none", "marker_size", "marker_fill" (default white), "point_labels": ["", "COP 3.2", ...] (one per point, null/"" to skip), "label_offset": [dx, dy], "label_anchor": "start"|"middle"|"end", "label_halo": "#ffffff"|"none", "label_font_size", "label_color", "font_family", "id", "layer"}. Labels: label_offset is from the point to the label's anchor, and the label is vertically CENTRED on point + dy (dy = 0 → centred on the point). Anchor defaults to start for dx >= 0, else end. Without label_offset the label goes right of the point, on the side the line is not heading to. Labels carry a halo stroke (default white) so the line can cross them — set label_halo "none" (or the background colour) for labels on dark fills; recolouring a label later does not remove its halo (use stroke: "none"). Ids follow the series id: -line, -marker-, -label- (k = 1-based point index). Returns per series those ids and the points in user units (for annotations); warns about points outside the grid.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gridNogrid
doc_idNo
seriesYes
previewNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does so well: it documents default behaviors (label anchored right of the point unless label_offset given, marker_fill default white, halo default white), side effects ('recolouring a label later does not remove its halo'), generated id conventions, and a warning about points outside the grid. It misses whether the document is mutated, and says nothing about doc_id/preview behavior.

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 purpose is front-loaded in the first clause, and the dense series/label/id detail is largely necessary given the 0%-coverage schema. It's a wall of text with heavy parenthetical nesting, but little is redundant.

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

Completeness3/5

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

For a complex plotting tool with no output schema and no annotations, the description covers series structure, label geometry and return ids/warnings well. It still leaves the grid/doc_id/preview parameters and the document-mutation semantics of the call unaddressed.

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

Parameters3/5

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

Schema coverage is 0%, so the description must compensate. It thoroughly documents `grid` ('that grid's id_prefix') and gives an exhaustive spec for each `series` entry, including keys, enums and defaults. However, `doc_id` and `preview` are entirely undocumented, leaving half the parameters unexplained.

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

Purpose4/5

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

States a specific verb+resource ('Plot data on a grid') and ties itself to a named sibling ('a grid made with the `grid` tool'), with the value proposition 'in DATA values — no coordinate maths' making the scope concrete. It's clear what the tool does, though it doesn't contrast against broader sibling drawing tools like add_elements.

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

Usage Guidelines3/5

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

The description implies usage via the prerequisite ('a grid made with the `grid` tool') and the value claim about avoiding coordinate maths, which tells the agent when this is preferable. However, there is no explicit when-not guidance or named alternative for non-grid-based plotting.

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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