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audit_typography

Read-only

Audit typographic scale, line-height consistency, and weight ladder of a web page or text nodes. Detects dominant ratio, body rhythm, and weight outliers.

Instructions

Audit the typographic SCALE of a rendered page (pass url) or a pre-collected snapshot of text nodes. Emits a focused report: (a) MODULAR SCALE — detects the dominant ratio (~1.2/1.25/1.333/1.5) across distinct font sizes and flags off-scale outliers; (b) LINE-HEIGHT CONSISTENCY — unitless lh/fs ratio per node, identifies the body rhythm and flags outliers; (c) WEIGHT LADDER — distinct weights, flags >4 weights or non-standard CSS values. Returns scale, line_height, weight_ladder, nodes_analyzed, and findings[{rule,severity,selector,message,fix}]. Goes beyond audit_page's pass/fail typography checks. url mode requires headless chromium.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoURL to render and measure (http/https or file://). Requires headless chromium.
nodesNoPre-collected text nodes to analyze without rendering.
Behavior4/5

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

Annotations declare readOnlyHint=true and destructiveHint=false, which the description does not contradict. The description adds behavioral context such as the return structure (scale, line_height, etc.) and the requirement for headless chromium in URL mode. It also explains that the tool emits a focused report, going beyond simple checks.

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 well-structured, starting with the overall purpose, then bullet-pointing the three audit aspects, and concluding with the return fields and a note about headless chromium. It is informative without being overly verbose; every sentence adds value.

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?

Given the tool's complexity (three audit dimensions) and the absence of an output schema, the description adequately explains the return value (scale, line_height, weight_ladder, etc.) and the structure of findings. It also mentions the distinction from 'audit_page', providing sufficient context for an AI agent.

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?

Both parameters are described in the schema (100% coverage), but the description adds meaningful context: it explains that 'url' requires headless chromium and that 'nodes' are pre-collected text nodes for analysis without rendering. This enhances understanding beyond the schema.

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 clearly states it audits the typographic scale of a rendered page or pre-collected snapshot, listing the three specific aspects (modular scale, line-height consistency, weight ladder). It explicitly distinguishes from the sibling tool 'audit_page' by noting it goes beyond pass/fail typography checks.

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

Usage Guidelines4/5

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

The description provides clear context: it mentions 'url mode requires headless chromium' and contrasts with 'audit_page' for simpler checks. It does not explicitly mention when not to use or list alternatives, but the guidance for when to use each mode is sufficient.

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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