Tollmint

legal_messaging

When a commercial email, SMS, or call may lawfully be sent, by channel and jurisdiction. The field that matters is consent_model: the US is opt-out for email, Canada and the EU are opt-in, and Germany applies opt-in to B2B while France and the Netherlands do not. Applying the US model abroad is a breach. Includes opt-out deadlines, permitted calling hours, whether a private right of action exists (the difference between a regulator fine and a class action), and the FCC one-to-one consent rule vacated a day before it took effect. Free — this call costs nothing. No account or payment required.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No
`search`	No	Free-text over summary, instrument and detail.
`status`	No	Filter to one lifecycle state.
`dead_only`	No	Return only rules that are NOT live law — vacated, superseded, or still proposed. These are the rules most often wrongly believed to be in force.
`jurisdiction`	No	Substring match, e.g. "EU", "UK", "US-federal", "California", "Germany".
`verified_only`	No	Only rows whose source URL resolved when last checked. Off by default: many primary sources (courts, national gazettes) block automated checkers, so "blocked" is not "bad".

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description partially discloses behavioral traits by explaining the data returned and key concepts like consent_model. However, it does not explicitly state that the tool is read-only, mention error handling, or discuss rate limits, leaving some transparency gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the purpose but includes detailed legal explanations that could be condensed. While informative, it is somewhat verbose for a tool description, and every sentence does not earn its place.

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 6 parameters and no output schema, the description provides substantial context about the tool's functionality, return contents, and jurisdictional nuances. It covers key aspects but lacks information on pagination or data freshness.

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 high (83%), so baseline is 3. The description adds value for parameters like dead_only and verified_only by explaining their significance and default behaviors. The limit parameter lacks additional context, but overall the description enriches parameter understanding.

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 the tool's purpose: determining when commercial email, SMS, or calls may lawfully be sent, by channel and jurisdiction. It includes specific examples like consent_model and distinguishes from sibling tools by focusing on messaging legality.

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 for usage, noting that the tool is free and requires no account or payment. It describes the content returned (opt-out deadlines, calling hours, etc.) but does not explicitly state when not to use it or suggest alternatives.

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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