Tollmint

psych_enforcement

Regulatory enforcement actions over deceptive interface design, each citing the regulator’s own document: the law and article, the company, the penalty, and what was actually on the screen. Includes dismissals, vacated rules and findings of lawfulness, which mark where the line sits and which fine-only lists omit. Also reports patterns prohibited but never enforced, and cases excluded for want of a primary source. Use to tell whether a design choice has cost anyone money, and where. Free — this call costs nothing. No account or payment required.

Input Schema

TableJSON Schema

Name	Required	Description
`outcome`	No
`pattern`	No	Pattern to look up. Accepts our taxonomy ids (roach-motel, fake-urgency, hidden-costs, trick-wording, forced-continuity) or enforcement terms (drip-pricing, preselected-consent, obstruction, privacy-zuckering, bait-and-switch, disguised-ads).
`min_penalty`	No	Minimum penalty in the record currency. Rows with no penalty are excluded.
`jurisdiction`	No	Substring match: "EU", "UK", "US-federal", "US-state", "France", "India".
`boundary_only`	No	Return only outcomes that bound the rule — dismissals, vacated rules, findings of lawfulness. These say what is permitted, which fines cannot.

TDQS

A4.3/5.0

Behavior5/5

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

With no annotations, the description fully discloses behavior: it is a read-only query ('Free — this call costs nothing. No account or payment required'), covers patterns never enforced, and excludes cases lacking primary sources. No contradictions.

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 longer but every sentence adds necessary detail (inclusions, exclusions, free access). It is front-loaded with the core function, then elaborates. Could be slightly trimmed but well-structured.

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?

No output schema, but the description explains return data composition (law, company, penalty, screen content) and includes excluded cases and unenforced patterns. Missing pagination or format details, but adequate for a list function.

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 80%, so baseline is 3. The description does not add meaning beyond the schema's parameter descriptions (e.g., enum values for outcome, pattern taxonomy ids). No extra semantic value.

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 specifies the verb 'regulatory enforcement actions' and the resource 'deceptive interface design', listing what each record includes (regulator's document, law, company, penalty, screen content). It distinguishes from sibling tools like psych_dark-patterns by focusing on enforcement outcomes including dismissals and findings of lawfulness.

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?

States 'Use to tell whether a design choice has cost anyone money, and where', and explains inclusions/exclusions (e.g., fine-only lists omit boundary rulings). While it lacks explicit when-not-to-use, the context is clear enough for an agent to infer appropriate use vs. other tools.

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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TDQS

A4/5.0

Disambiguation5/5

All 20 tools have clearly distinct purposes, grouped by domain prefixes (content_ai, design_ai, legal, psych, ref, tollmint, web). Even similar-sounding tools like psych_dark-pattern-detect and psych_dark-patterns are differentiated as a live scanner versus a reference taxonomy. No two tools overlap in functionality.

Naming Consistency4/5

Naming mostly follows a prefix_descriptive pattern, but some tools use hyphens (content_ai-score, design_ai-slop-detect) while others use underscores (legal_accessibility, psych_biases). This minor inconsistency prevents a perfect score, but the pattern is still clear and readable.

Tool Count4/5

20 tools is slightly above the typical 'well-scoped' range, but each tool serves a specific, justifiable need across multiple domains (legal, psychology, content analysis, geocoding, internal). The count feels comprehensive rather than bloated.

Completeness5/5

The tool surface covers all major areas implied by the domain prefixes: comprehensive legal compliance references, extensive psychology/behavioral design tools, content and design analysis, geocoding, and internal server management. No obvious gaps for the intended use cases.

Resources

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