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Glama
HalidSaglam

saglitzdesign-mcp

by HalidSaglam

Audit Ux Copy

audit_ux_copy
Read-onlyIdempotent

Audit UI and marketing copy for readability, passive voice, jargon, filler, and weak CTAs. Receive metrics with flagged phrases and fixes.

Instructions

Audit UI / marketing copy objectively: readability (Flesch reading ease + grade level), average sentence length, passive voice, jargon/hype words, filler, user-focus ('you' vs 'we'), and weak CTAs. Returns metrics plus specific flagged phrases and fixes. The machine-checkable slice of UX writing — pair with get_design_doc('ux-writing') for voice/tone judgment. It reads source and does not measure anything: no usability session is run, no A/B result is read, and no finding here is or can be a statement about whether the copy actually works for a reader. It also has no notion of register: it has no way to tell short UI copy from long-form prose, so a paragraph of accurate technical documentation can draw more jargon/filler hits than a paragraph of real hype. Returns markdown plus structured output: findings (rule, severity, message, fix, doc, line), a severity summary, a machine-readable notVisible list of what it could not check, and a metrics block carrying the same words/sentences/avgSentenceLen/Flesch/grade-level/you-we numbers the markdown table prints.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe copy to audit (a headline, paragraph, button label, error message, or full page copy)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricsYesThe metrics table the markdown half prints, as numbers. Facts about the text's shape, not measurements of how it reads — see `notVisible`.
summaryYesCounts by severity. Always agrees with `findings` — it is derived from the same list.
findingsYesEvery finding, in the order the markdown report lists them.
notVisibleYesWhat this audit structurally could not check, one limitation per entry. Read it as a peer of `findings`: silence on a subject named here is this tool's reach, not a clean result. Nothing any of these tools reports is measured.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.28.0

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses important non-obvious behaviors: it reads source and does not measure anything, has no concept of register, and may falsely flag technical documentation for jargon/filler. This significantly shapes how an agent should interpret results.

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 information-dense and front-loads purpose, but the final sentence enumerating the output structure is verbose and partially redundant with the markdown/metrics repetition. Every sentence does add value, though the length is slightly more than needed.

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?

For a single-parameter tool with an output schema, the description thoroughly covers the return shape, limitations, and relationship to sibling tools. An agent has everything needed to call it correctly and interpret its results.

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?

The schema already provides full coverage for the single 'text' parameter with concrete examples of acceptable input. The description adds no additional parameter-level semantics, so the baseline of 3 applies.

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 starts with a specific verb ('Audit') and a well-defined resource ('UI / marketing copy') followed by an explicit list of metrics. It also distinguishes itself from the voice/tone-oriented sibling get_design_doc, making its scope clear among many audit_* tools.

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?

The description explicitly says to pair with get_design_doc('ux-writing') for voice/tone judgment, giving a clear alternative for non-machine-checkable aspects. It also specifies what the tool cannot do (no usability claims, no register awareness), which helps an agent decide when not to use it.

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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