Public Root Data dental analytics directory for DSOs, dental practices, blog, and FAQ tools.
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Average 3.8/5 across 8 of 8 tools scored. Lowest: 3.2/5.
Each tool targets a distinct action and resource type: search, get, compare, list, FAQ, and blog search are clearly separated, and entity types (DSO vs practice vs blog vs FAQ) are explicit. No two tools have overlapping purposes that could cause misselection.
Seven of eight tools follow the verb_noun pattern (compare_dsos, get_dso_profile, search_practices, etc.), while root_data_faq deviates as a noun phrase with no leading verb. This is a minor inconsistency in an otherwise predictable scheme.
With 8 tools, the set is well-scoped for a public directory server. Each tool earns its place, covering search, retrieval, comparison, ranking, and informational queries without redundancy or bloat.
For a read-only public directory, the surface is complete: both DSOs and practices have search and get operations, plus compare and list ranking for DSOs, and FAQ and blog search fill informational gaps. No critical operations are missing; optional search parameters ensure broad coverage.
compare_dsosCompare DSOsAInspectCompare two Root Data public DSO directory profiles by slug using public profile summaries, regions, websites, and public signal counts.
| Name | Required | Description | Default |
|---|---|---|---|
| dso_slug1 | Yes | ||
| dso_slug2 | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It reveals the data sources (public profile summaries, regions, websites, signal counts) but does not state whether the operation is read-only, how missing or invalid slugs are handled, or what the output format looks like. Significant gaps remain for a tool with no structured annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no wasted words. It conveys the action, target, and compared aspects in under 20 words, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-param comparison tool, the description covers the core functionality and data used. However, with no annotations, output schema, or usage guidance, it lacks behavioral and edge-case details, making it adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates by clarifying that both parameters are slugs for the two DSO profiles to compare. This adds meaning beyond raw param names, though it doesn't explain slug format beyond schema maxLength.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Compare' and the resource 'two Root Data public DSO directory profiles by slug', with specific attributes (summaries, regions, websites, signal counts). This distinguishes it from siblings like get_dso_profile, which fetches a single profile.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when comparing two specific DSO profiles by slug, but provides no explicit guidance on when to choose this tool over siblings like get_dso_profile or search_dsos. No exclusions or alternative scenarios are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_dso_profileGet DSO ProfileAInspectGet one public Root Data DSO directory profile by slug. Returns public website, region, profile URL, summary, and public signals.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It states the data is 'public' and lists return fields, implying a safe read operation. However, it does not mention potential errors, authentication needs, or any quirks such as missing profiles or data limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, immediately states the action and resource, and lists return fields with no redundancy or filler. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter get operation, the description covers the core purpose, return values, and public nature. It lacks details about slug format or how the return data might vary, but these are minor gaps given the low complexity and presence of sibling search tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter 'slug' with 0% description coverage, so the description must explain its meaning. The description mentions 'by slug' but does not define what a slug is, its format, or how to obtain a valid value. This falls short of compensating for the schema's lack of semantic detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get'), names the exact resource ('one public Root Data DSO directory profile'), and specifies the lookup method ('by slug'). It also lists the returned fields, making it distinct from sibling tools like 'get_practice_profile' and 'search_dsos'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: when you have a slug and want a single public profile. However, it does not explicitly mention when not to use it or offer alternatives like 'search_dsos' or 'compare_dsos'. The context is inferable but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_practice_profileGet Practice ProfileAInspectGet one published public dental practice directory profile by slug. Returns public website, locations, services, rating summary, and profile URL.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It explicitly lists the returned data fields and limits the scope to 'published public' profiles, setting clear expectations. It does not mention error handling or authentication, but the read-only nature is evident from the verb 'get' and the 'public' qualifier.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence (22 words) that front-loads the action and resource, states the selection method, and enumerates the return fields. Every phrase earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool with no output schema, the description covers the essential aspects: identification method ('by slug'), scope ('published public'), and return contents. It does not specify error scenarios, but given the simple get semantics, this is not a critical omission.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero parameter descriptions, so the tool description must compensate. It confirms the parameter's purpose ('by slug') but adds no format details, examples, or constraints beyond the schema's min/max length. This is a minimal but adequate contribution.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' with the resource 'one published public dental practice directory profile', and explicitly states the selection method 'by slug' and the return contents (public website, locations, services, rating summary, profile URL). This clearly distinguishes it from sibling tools such as get_dso_profile (different entity) and search_practices (search vs. direct fetch).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a clear usage context: use this when you have a specific slug and need a single published public practice profile. It does not explicitly state exclusions or alternatives, but the 'by slug' scoping makes the intended use unambiguous among the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_top_dsosList Top DSOsAInspectList public DSO directory profiles ranked by public size, locations, or growth signals inferred from public profile text. Results are directional, not a private operating benchmark.
| Name | Required | Description | Default |
|---|---|---|---|
| by | Yes | ||
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavioral traits. It explicitly notes that results are directional and inferred from public profile text, alerting users to the non-authoritative nature of the data. This adds significant context beyond the basic function, though it stops short of describing return format or pagination.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action and ranking criteria, followed by a valuable caveat. Every word earns its place, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no output schema and no annotations, the description covers the core purpose, ranking dimensions, and data reliability. It does not specify the exact response structure, but for a listing tool this is a minor gap, as the agent can infer the output from the name and sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains the 'by' parameter with the ranking criteria and clarifies 'growth signals' as inferred, adding meaning beyond the schema's enum. However, it does not explain the 'limit' parameter or default behavior, and with 0% schema description coverage, the description only partially compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists public DSO directory profiles with ranking by size, locations, or growth signals. This is a specific verb-resource-scope combination that distinguishes it from sibling tools like search_dsos or get_dso_profile, though it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus sibling tools like search_dsos or compare_dsos. The caveat 'Results are directional, not a private operating benchmark' provides interpretation context but not usage direction. The intended use is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
root_data_faqRoot Data FAQBInspectAnswer common public questions about Root Data services, DSO directories, dental practice benchmarks, AI Coach, integrations, privacy, demos, and pricing.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states that the tool answers questions and lists topics, but does not explain how answers are generated, whether sources are cited, what the output format is, or how parameters affect results. This lack of behavioral detail is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence (19 words) that front-loads the purpose and lists topics without any redundant phrases. Every word contributes to defining the tool's scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but the description omits behavioral specifics such as return format, parameter usage, and expected output. Since there is no output schema or annotations, the description should explain what the agent receives and how the tool behaves. The topic list provides some context, but gaps remain, making it minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has two parameters (limit, query) with no descriptions, and the description does not mention them at all. With 0% schema coverage, the description must compensate, but it provides no guidance on what 'query' should contain or what 'limit' controls. The agent cannot infer meaningful parameter semantics from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool answers common public questions and enumerates specific topics, distinguishing it from sibling tools like search_dsos and list_top_dsos. The verb 'Answer' and the resource 'common public questions' make the purpose specific and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies an FAQ tool but does not explicitly state when to use it versus alternatives. There is no mention of 'use for general questions' or comparisons to siblings. The role is inferred from the name and context, so the usage guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_blog_articlesSearch Blog ArticlesAInspectSearch published Root Data blog articles by title, slug, excerpt, category, tag, or SEO summary. Supports DSO-only, practice-only, both-audience, or all articles.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | ||
| audience | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden of behavioral disclosure. It only reveals that 'published' articles are searched and audience filtering is supported, but does not explain return format, pagination, sorting, or behavior with empty queries. This is minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundant wording. It efficiently packs the searchable fields and audience options without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with 3 parameters and no output schema, the description covers the core search scope and audience filter. However, it lacks details about result format, edge cases (e.g., empty query), and any dependencies or prerequisites, making it not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning. It explains the 'query' parameter by listing searchable fields and defines the audience enum values (DSO-only, practice-only, both, all). However, 'limit' is not described, leaving some semantic gap. It partially compensates for the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches published Root Data blog articles, listing specific searchable fields (title, slug, excerpt, category, tag, SEO summary). This distinguishes it from sibling tools that search DSOs/practices, ensuring no ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that this tool is for searching blog articles, which implicitly distinguishes it from sibling tools for other data types. However, it does not explicitly name alternatives or specify when not to use this tool, so it falls short of the highest bar.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_dsosSearch DSOsAInspectSearch Root Data's public DSO directory by organization name, slug, website, summary, or public website signals. Returns public directory data only.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden but only discloses that it returns public directory data and lists searchable fields. It does not explain matching semantics, pagination, rate limits, or authentication, leaving some behavioral uncertainty. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the core purpose and scope without wasted words. Every phrase adds value, and it is easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple two-parameter schema and no output schema, the description provides sufficient context for a basic search tool. It identifies what can be searched and that results are public directory data, though it omits any details about the response format or default limit. This is complete enough for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for its 2 parameters, but the description compensates by explaining that 'query' can search by organization name, slug, website, summary, or public website signals. However, it does not clarify the 'limit' parameter's behavior or any defaults, so compensation is partial.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Search' and identifies the resource 'Root Data's public DSO directory' with explicit searchable fields (name, slug, website, summary, public website signals). It clearly distinguishes from siblings like search_practices and list_top_dsos by specifying the target directory and scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that this is for searching public DSO directory data, and the phrase 'public directory data only' signals a boundary. However, it does not explicitly name alternatives or when-not-to-use, though sibling tools like search_practices are available in context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_practicesSearch Dental PracticesAInspectSearch Root Data's public dental practice directory. Supports query, service, location, city, state, minimum Google reviews, minimum star rating, and sorting by Google review count or rating. Returns published public listings only. All parameters are optional.
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | ||
| limit | No | ||
| query | No | ||
| stars | No | ||
| state | No | ||
| sortBy | No | ||
| reviews | No | ||
| service | No | ||
| location | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states 'Returns published public listings only' and 'All parameters are optional', both important constraints. It does not discuss pagination, default limits, or authentication, but the 'public' label implies no auth and the transparency is adequate for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, front-loading the primary purpose and then listing filters and constraints. Every sentence adds value, and there is no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with no output schema and no annotations, this description is sufficiently complete. It covers the core behavior (public, published-only listings), all optional parameters, and the available sorting options. Minor gaps like pagination behavior or default sort order are not critical for correct invocation, so this is above the minimum but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Since the input schema has no descriptions, the description compensates by explaining the meaning of most parameters: query, service, location, city, state, minimum Google reviews (reviews), minimum star rating (stars), and sorting by review count/rating. It omits 'limit' but that parameter is self-explanatory. This is solid semantic coverage for a schema with zero descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Search Root Data's public dental practice directory' with a specific verb and resource. It distinguishes itself from sibling tools like search_dsos by focusing on practices rather than DSOs, and the mention of 'Returns published public listings only' adds scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: it is used to search public dental practice listings, implying it is the right choice for practice lookups rather than DSO comparisons. However, it does not explicitly name alternative tools or say when not to use it, so it lacks the explicit exclusions needed for a 5.
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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