Enterprise account-research resources, product information and reproducible corporate-group samples.
Scored across 3 tools
The three tools target fairly distinct facets: sample data inspection, product/pricing info, and documentation links. However, all three are read-only informational tools with subtle boundaries (product information vs. public resources overlap somewhat), which could cause occasional misselection.
All tools follow a consistent verb_noun pattern (get_, get_, list_) with a uniform snake_case style and shared EntityReach prefix. Naming is predictable and readable throughout.
Only 3 tools for a 'Corporate Group Intelligence' product is thin; the surface reads more like a documentation/info shell than a functional data server. It is not extreme, but feels under-scoped for the stated domain.
There is no tool to actually query ownership structures, resolve entities, or retrieve live corporate group data—only a static sample, product info, and docs. This is a significant gap that will block agents expecting to perform the server's apparent core function.
Inspect reproducible counts, field availability and limits in the existing static Alphabet group sample. This is not live ownership data or a full coverage benchmark.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds genuinely useful context beyond that: the data is a static sample, it is not live ownership data, and it should not be read as a coverage benchmark — key expectations for interpreting results.
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?
Two sentences, zero waste, with the positive scope stated first and the caveat second. Nothing is padding.
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 no-parameter, no-output-schema read tool, the description covers what is returned (counts, field availability, limits) and the freshness caveat. It is a bit thin on the shape/format of the returned counts, but that gap is minor for a simple inspection tool.
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 tool takes zero parameters, so per the rubric the baseline is 4. The description adds no parameter detail but none is needed; it cannot improve on an empty schema.
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 names a specific verb (inspect) and resource (the static Alphabet group sample) and enumerates what is inspected: reproducible counts, field availability, and limits. It does not reference the sibling tools, but the scope is distinct enough from get_entityreach_product_information and list_entityreach_public_resources that an agent can differentiate it.
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?
It gives an explicit negative boundary — 'not live ownership data or a full coverage benchmark' — which steers the agent away from treating results as authoritative live data. It does not, however, name an alternative tool for when live ownership data is actually needed, so routing guidance is one-sided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read public EntityReach product capabilities, pricing, access requirements and limitations. Does not access a private workspace or live company records.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, and non-open-world behavior, so the safety profile is covered. The description adds genuine scope disclosure beyond that — that this reads static public material and never touches workspace or live records — which is useful for an agent deciding whether the answer is authoritative for a specific company.
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?
Two sentences, no filler, with the positive scope front-loaded and the exclusionary scope second. Every clause 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?
A parameterless read-only lookup with no output schema and full annotation coverage needs little more than what is given: the description says what content is returned and what is explicitly out of scope. Nothing an agent needs in order to call or trust it is missing.
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 tool takes zero parameters, so the baseline is 4; there is no parameter syntax the description could usefully add. It appropriately spends its words on scope instead of restating an empty schema.
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?
States a specific verb and resource — reading public EntityReach product information — and enumerates the content covered (capabilities, pricing, access requirements, limitations). It distinguishes itself from siblings only indirectly via the 'public' scope rather than naming a specific sibling tool, so it falls short of a 5.
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 second sentence provides an explicit when-not condition: it does not access a private workspace or live company records, which is exactly the boundary separating it from sibling tools that return company/group data. No alternative tool is named, keeping it out of 5 territory, but the usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Find public EntityReach documentation, enterprise account-research guides, coverage methodology and contact links.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds only the mild signal that the resources are 'public' (no auth implied) and the content categories; it says nothing about whether it returns links, documents, or paginated results.
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 filler, and the key qualifier ('public') appears early. The trailing list of resource categories is slightly dense but each item adds scope information.
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 parameterless, read-only listing tool with full annotation coverage and no output schema, the description supplies enough for an agent to know what it will surface. The one residual gap is return shape (links vs. content), which is only hinted at by 'contact links'.
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 tool takes zero parameters, which is the baseline-4 case; there is nothing for the description to disambiguate. The schema is trivially complete (no properties, additionalProperties false).
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 names a specific verb ('Find') and enumerates the resource types returned (documentation, account-research guides, coverage methodology, contact links), which is more informative than the generic name alone. It stops short of distinguishing itself from the siblings (get_entityreach_product_information, get_entityreach_group_sample_analysis), so an agent cannot tell from the text why it would pick this over those.
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 guidance on when to call this versus the two sibling tools, and no prerequisites or exclusions are stated. The only implied cue is 'public', leaving the agent to guess whether this is the discovery entry point or a supplementary call.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
get_entityreach_group_sample_analysisget_entityreach_product_informationlist_entityreach_public_resourcesSales intelligence — research companies, qualify prospects, and find contacts.
Verified company profiles, financials, ownership, registry records and business contacts.
Evidence-aware supply-chain research. Authentication required: OAuth or a client-stored API key.
Add one secure layer between your agents and this server.
