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by com.allthepossibles
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Cognitive load check

cognitive_load_check
Read-only

Static audit of how much a screen asks of a person. Pass content as HTML (best) or plain text. Reports interactive controls per screen, words, sentence length, an English reading-ease estimate, long paragraphs, missing headings, and form length, then checks WCAG 2.2 criteria that matter for cognition: 2.2.1 Timing Adjustable (meta refresh, countdown and session language), 3.3.8 Accessible Authentication Minimum (paste or autofill blocked, CAPTCHA or puzzle language), 3.3.7 Redundant Entry (confirm fields), 3.3.2 Labels or Instructions (placeholder-only fields, unexplained required fields), 1.3.5 Identify Input Purpose (missing autocomplete tokens) and 3.2.2 On Input. Count and length thresholds are conventions and are labeled so. Reads the pasted source only; nothing is rendered or run, stored or logged.

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": {
      "content": "<content>"
    },
    "name": "cognitive_load_check"
  }
}

Input Schema

NameRequiredDescriptionDefault
contentYesHTML of the screen, or plain text of its copy. Up to 100,000 characters on the free tier.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Goes well beyond the readOnly/closed-world annotations: it states the source is only read, nothing is rendered, run, stored, or logged, and that count/length thresholds are conventions and labeled as such. That last point is unusually candid about result reliability and is exactly the kind of context annotations cannot convey.

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?

Purpose is front-loaded in the first sentence and the input instruction comes early; the long enumeration of criteria is dense but each item is substantive given there is no output schema. The WCAG parentheticals are slightly heavy but earn their place by specifying detection targets.

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?

With no output schema, the description carries the burden of describing returns, and it does so by enumerating the metrics and criteria reported. Combined with the single documented parameter and the no-storage disclosure, an agent has everything needed to call and interpret it.

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?

Schema coverage is 100% and the schema already documents the HTML-or-text input and the 100,000-character limit. The description adds a mild prioritization ('HTML (best)') that the schema does not express, giving slight value above the baseline.

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 specific verb and resource ('static audit of how much a screen asks of a person') and then enumerates exactly what is measured, including named WCAG 2.2 criteria. This is distinguishable from the many sibling auditors (audit_form, plain_language_check) because the scope is cognitive load and cognition-specific success criteria.

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?

It gives input guidance ('Pass content as HTML (best) or plain text'), which is invocation help, and usage is implied by the metric list. But it never says when to prefer this over audit_form, check_form, or plain_language_check, nor any exclusions or prerequisites. Adequate but with a clear routing gap in a crowded sibling set.

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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