Nombrio Clearance Check

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

The annotations already mark the tool as read-only and open-world, and the description adds substantial behavioral context: live registry data, free access, no API key, shared fair-use pool with per-caller daily allowance, and a not-legal-advice disclaimer. It also reveals that Instagram returns only a confirm-link, which is a specific non-obvious behavioral detail.

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 long but densely informative; every sentence contributes operational or selection-critical information. The core use case is front-loaded, followed by enumerated data coverage, alternative-tool routing, and practical caveats. No filler or tautological phrasing.

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 tool's moderate complexity, the description covers what it does, when to use it, what data sources are included, what the caller can expect in terms of output categories, the existence of a full interactive result, limitations, and the availability constraint. With the input schema and output schema present, nothing essential for correct invocation 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 schema already describes the single parameter fully with formatting constraints and an example, giving 100% schema description coverage. The tool description adds additional semantic value by clarifying that the input should be a brand, business, product, or app name, and that the tool handles exactly one name, which supplements the schema without redundancy.

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 states a specific action and resource: run a free Clearance Check on ONE name, and enumerates exactly what checks are performed (trademark, domain, social handles, dev namespaces, app store). It clearly distinguishes itself from the plural sibling tool check_names by emphasizing 'ONE' name, making it easy for an agent to select correctly.

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 explicit when-to-use guidance: 'Use it when the user asks whether a SPECIFIC name is taken, trademarked, available or safe to use.' It also names the alternative explicitly — 'For a shortlist or comparison use check_names instead' — and explains the tradeoff. This is exemplary routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Beyond the readOnlyHint and openWorldHint annotations, the description discloses live parallel execution, per-name verdicts, ranked summary, full-result links, and fair-use pool consumption. The 'not legal advice' caveat also provides helpful real-world context.

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 main action, use cases, and distinction from check_name are front-loaded and each sentence contributes meaningful context. It is longer than the bare minimum, but the extra details about fairness pool, legal caveats, and parallel execution are justified.

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 batch screening tool, the description is complete: it covers input requirements, behavior, output shape, relationship to sibling tools, and constraints. It would not be complete for a mutation or stateful workflow, but this is a read-only broad matching tool and the output schema covers return structure.

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 coverage is 100%, and the schema already documents the 2-8 item range, min/max length, plain-names-only requirement, and deduplication. The tool description reinforces the purpose but does not add substantive new parameter-level semantics beyond the 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 states a specific verb and resource: screen 2-8 candidate names in one call and return them ranked by viability. It clearly differentiates itself from the sibling check_name by emphasizing parallel batch execution of the same data.

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 explicitly explains when to use the tool: whenever the user is brainstorming, has a list, or asks which of several names is available or safest. It also states that one check_names call replaces many check_name calls, giving clear selection guidance against its sibling.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations declare readOnlyHint=true, and the description is consistent with that, describing a polling/read operation. It adds useful behavioral context by disclosing the API key requirement and the fallback behavior when no key is provided, which is information not present in the 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?

Two tightly packed sentences deliver all the essential information: prerequisite, behavior, output structure, and sibling interaction. Every clause adds value and there is no filler or repetition of schema fields.

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 single-parameter polling tool with a rich output schema and readOnly annotation, the description is complete. It covers authentication, statuses, output content, and a related tool, leaving no significant gaps for a correct call.

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 already provides full coverage for the single parameter, sessionId, stating it comes from start_naming_session. The description reinforces that provenance and adds the requirement context, which gives an agent a slightly richer understanding of the parameter's origin.

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 identifies the tool as one that polls the status of a Naming Session, lists the specific status values, and describes the output content. It distinguishes itself from sibling tools by naming start_naming_session as the origin of the session and positions check_name as a complementary deeper check.

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 states that a connected plan/API key is required, describes when to use it (polling a session started with start_naming_session), and points to check_name as a companion for deeper analysis. It does not explicitly state when not to use this tool, but the context is clear enough for an agent to select it appropriately.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Behavior is well exposed beyond annotations: the tool is asynchronous, returns a sessionId, takes 1–3 minutes, must be polled every 10 seconds, consumes one plan credit, and behaves in a documented way without an API key. This addresses side effects, quota usage, and failure edge cases.

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?

Three dense sentences cover prerequisites, purpose, output, polling behavior, plan cost, and no-key behavior. Every sentence earns its place with no filler or 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?

The description covers all operational essentials: auth, plan consumption, async flow, polling interval, latency, and no-key behavior. It is mostly complete for an output-schema-bearing tool, but the lack of semantic guidance for the optional params leaves a material gap.

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 only 33%. The description re-adds context for the brief parameter, but the two more nuanced parameters, abstractionLevel and soundPersonality, have no descriptions beyond their enum names. The tool description does not compensate for this gap or explain how to choose those values.

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 states a specific verb and resource: it starts a Nombrio Naming Session, generates up to 8 name ideas from a brief, and pre-clears them. It also distinguishes itself from siblings by naming get_naming_session as the polling tool and comparing its registries to check_name.

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 use context: it requires a connected plan, consumes one Naming Session credit, is asynchronous, and should be polled via get_naming_session. It does not explicitly state when to prefer this over the sibling check tools, so it stops short of a full 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.