SignatureForever

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

With no annotations, the description carries the burden and mostly delivers: it discloses the multi-client behavior, the fine-grained output (per-client verdicts, rule, why, fix), and the no-account requirement. It doesn't explicitly discuss side effects, but an auditing tool's read-only nature is clearly implied and no auth/rate-limit surprises are indicated.

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 tight sentences: what the tool does, what it returns, when to use it, and access requirements. Every sentence contributes and the most important action verb is front-loaded.

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?

With only one input parameter and a rich description of the return behavior (per-client verdicts, problems, rules, fixes), plus use cases and access requirements, an agent has everything needed to select and invoke this tool correctly.

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 documents the html parameter as 'the full HTML of the email signature,' and the description's wording 'Audit any email-signature HTML' aligns with that. Since schema coverage is 100%, the baseline of 3 applies; no additional format or example detail is provided 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 ('Audit'), a precise resource ('email-signature HTML'), and names the exact target clients (Gmail, Outlook, iOS Mail, etc.). This clearly distinguishes it from the sibling tools like create_email_signature or list_signature_templates.

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?

Explicitly gives trigger scenarios: when a signature is broken, images don't render, Outlook layout fails, or before sending. It does not name alternatives or provide exclusion criteria, but the when-to-use guidance is unambiguous and actionable.

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?

With no annotations, the description carries the disclosure burden. It reveals concrete behavioral traits: output is tables-only with inline CSS and fixed widths, Gmail rejects base64 images, and the free output appends a credit line. This goes well beyond the name, though it doesn't discuss failure/error behavior.

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 sentences with no filler: the first front-loads the action, the second layers on compatibility constraints, and the third handles pricing/next step. Every sentence 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 tool with 14 parameters and no output schema/annotations, the description covers the core behavior and key constraints but leaves out defaults, template selection details, and error scenarios. It is adequate for a basic call with full_name, but not complete for advanced usage.

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 43%, but the description does not compensate. It mentions absolute-URL images and the credit line, which loosely maps to photo_url and language, yet most parameters (city, phone, company, website, socials, accent_color) receive no additional semantics beyond their field names.

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 opens with a specific verb and resource: 'Build ready-to-paste email-signature HTML from a person's details.' This clearly differentiates it from siblings like check_email_signature and email_client_compatibility_matrix, since it's about generating rather than verifying or comparing.

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 makes the generation use case explicit and even routes to get_pricing when someone wants to remove the credit line. It doesn't explicitly exclude alternatives, but the build-vs-check/compatibility/list split is evident from the wording.

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?

With no annotations provided, the description carries the burden of behavioral disclosure. It reveals the output behavior well: 'Each row says yes/no/partial for seven real clients and explains what goes wrong.' This is meaningful beyond the tool name, though it does not describe filtering behavior in 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 compact and front-loaded with the tool's identity as a support matrix. Each sentence adds distinct information: what it covers, how rows are structured, and when to use it. There is no redundant 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 read-only lookup tool with one optional parameter and no output schema, the description gives sufficient context: supported topics, client count, row semantics, and the purpose. It does not specify the exact return data structure, but the 'each row says yes/no/partial' phrasing covers the essential output expectations.

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 already documents the optional 'feature' filter with 100% coverage. The description adds value by enumerating concrete feature names an agent might query (tables, flex/grid, background-image, etc.), effectively expanding the known parameter vocabulary beyond the schema's two examples.

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 a support matrix for HTML/CSS features affecting email signatures and states its use case: 'Use it to answer questions about email HTML support.' The explicit feature list and per-client yes/no/partial format distinguish it from sibling tools like check_email_signature or create_email_signature.

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 for when to use the tool: to answer questions about email HTML support and client-specific rendering. It does not explicitly name alternatives or state when not to use it, but the sibling tool names make the intended role obvious.

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?

No annotations exist, so the description carries the full burden. It discloses the tool's content coverage (plan features, costs, buy link) and one behavioral policy (hosted images when payments stop), but does not mention response format, whether output is a table/link, or pricing units. Adequate with notable gaps.

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 with zero waste: the first sentence states output content, the second gives concrete trigger examples. The most actionable usage guidance is front-loaded after a crisp subject line, and 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?

For a zero-parameter tool with no output schema, the description covers the returned content and the exact question types that invoke it, which is the substantive burden. Minor gaps such as response format and whether prices have recurring subscriptions are low-stakes given the tool's simplicity.

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 has zero parameters, and schema description coverage is 100% because the schema is empty. The description adds value by naming the resource the call retrieves, which is the relevant semantic contribution for a no-parameter tool; this matches the 0-param baseline.

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 explicitly states the resource (SignatureForever plans) and content (what each plan includes, costs, buy link, and credit-line removal pricing). It distinguishes cleanly from siblings: check_email_signature, create_email_signature, email_client_compatibility_matrix, and list_signature_templates are all about signature mechanics, not pricing, so an agent can differentiate without opening schemas.

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 explicit 'Use it when...' triggers with three concrete user questions (credit-line removal cost, signature count, hosted-image behavior on nonpayment). It lacks when-not-to-use guidance and does not name alternatives, but the siblings are so different in domain that the omission is minor.

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?

No annotations are provided, so the description carries the burden. It discloses that the tool returns information about templates (good for and width in pixels), but it doesn't mention return format or any side effects. Since it's a listing operation, it's likely safe, but the description doesn't explicitly state that it is read-only or non-destructive. It adds some value beyond the annotations (which are absent) but not a full behavioral profile.

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 that front-loads the key info: these are layouts for create_email_signature. It is efficient and doesn't waste words. It could be structured slightly better by starting with 'Lists' but it's still clear and brief.

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?

With no output schema and no annotations, the description needs to explain what the tool returns. It does mention the content (layouts, good for, width), but it doesn't specify if the return will be a list of objects, IDs, or how to reference them. Since it's a simple listing tool with no params, this is acceptable but not fully complete. The description gives enough for an agent to know its purpose, but the return format 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?

There are no parameters, so the description doesn't need to explain parameters. The baseline for 0 params is 4, and the description adequately explains what the output will contain (layouts, what each is good for, width in pixels), which is useful for the agent to interpret the return value. It doesn't describe the return structure, but with no parameters it's fine.

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 the tool lists signature templates and what they are good for, with width in pixels. It references a specific use case 'pass to create_email_signature' which gives context, but it doesn't explicitly define the purpose as 'list available templates' in a standalone way. It is clear but could be more specific about the action of listing.

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: to know what to pass to create_email_signature. It doesn't mention when not to use it or alternatives, but since there are no sibling tools that do something similar, the implication is adequate. It could be improved by stating that this is the direct source for template IDs, but it is not misleading.

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