Quattr

render_chart

Render an INTERACTIVE chart inline (line/area/bar with a type-switcher, hover tooltips, a footer metadata strip, and an "Open in Quattr" deep-link) from a prior verb's result rows. A sibling of build_chart_spec — pass the rows you already have; no re-query. Optionally pass deep_link to point the "Open in Quattr" link at the right destination + dates (Growth Trends, Competitive Trends, or AI Visibility). For AI-answer coverage-gap or cited-URL charts, use the AI Visibility destination (tab=prompts or tab=citedUrls) — never organic Growth Trends. DO NOT re-chart a verb result that already rendered a chart card — trend results (e.g. search_performance with granularity) auto-render a card that carries its own Open-in-Quattr link, so calling this again just duplicates the visual. Use this for rows that did NOT render (e.g. the advanced analytics query tool) or when the user explicitly asks for a different chart.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "rows": "<rows>"
    },
    "name": "render_chart"
  }
}

Input Schema

Name	Required	Description	Default
`x`	No
`y`	No
`mark`	No		line
`rows`	Yes	The rows array from a previous query result
`adhoc`	No	Adds an "Open in Adhoc Analysis" link that reopens the exact saved analytics query behind these rows in QWA's Adhoc Analysis section — echo queryExplore + queryQid from the verb result that produced the rows. Complements deep_link (which targets the trends pages); pass both when available.
`title`	No
`deep_link`	No	Where "Open in Quattr" should land (page + dates). Use ai-visibility for AI-answer charts (coverage gaps → tab=prompts; cited URLs → tab=citedUrls) — never growth-trends for those rows. Pass metric/granularity/filters too for a full-fidelity Growth / Competitive page. Omit for a generic growth-trends link. Keep the link CONSISTENT with the chart: date_range = the rows' effective window (see date_range), and title the chart by that same window.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 19, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations only carry the safety triple (readOnlyHint=false, destructiveHint=false, openWorldHint=false); the description adds real behavioral context beyond them: that it renders inline, that trend results with granularity auto-render their own card, and that the deep-link must stay consistent with the chart's date window. It doesn't explain pagination/return shape, but as a UI-rendering tool the key side-effects are disclosed.

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?

Front-loads the core purpose and then layers constraints in a logical order (sibling → when-to-use → destination rule → when-not). It is dense and parenthetical-heavy, but each sentence carries a distinct instruction rather than restating the name or schema.

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

Completeness4/5

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

For a 7-param tool with nested objects and no output schema, it covers the critical routing decisions, deep-link fidelity, and duplication avoidance. The remaining gap is x/y axis semantics, which neither the schema nor the description explains; otherwise an agent has enough to call it correctly.

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

Parameters4/5

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

With schema coverage at only 43%, the description compensates well: it explains deep_link destinations (growth-trends / competitive-trends / ai-visibility and the tab mapping), the consistency rule (date_range = rows' effective window), and echoes adhoc's queryExplore+queryQid fields. It leaves x/y undocumented, so it doesn't fully close the coverage gap, but adds substantial meaning for the complex nested params.

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?

States a precise verb (render) plus resource (interactive line/area/bar chart inline) and enumerates the concrete artifacts it produces (type-switcher, tooltips, footer strip, Open-in-Quattr link). It explicitly positions itself against its sibling build_chart_spec, so an agent can distinguish the two without opening either schema.

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?

Gives explicit when-to-use ('rows that did NOT render, e.g. the advanced analytics query tool' or an explicit user request) and when-not ('DO NOT re-chart a verb result that already rendered a chart card — calling this again just duplicates the visual'). It also routes the AI-visibility case to a specific destination and names the alternative sibling, leaving nothing to inference.

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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