LifeStep Workbook, Email, QR and DNS Tools

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

The description adds an important security-relevant behavioral detail beyond the annotations: the returned SVG markup must be treated as untrusted text and should not be executed or rendered automatically. It also states that no resource is created or modified, reinforcing the read-only, non-destructive annotation hints without contradicting them.

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 primary purpose, followed by the essential security warning and a side-effect clarification. Every sentence contributes meaningful information without redundancy or 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 simple single-parameter tool with no output schema, the description is sufficiently complete: it identifies the action, the API, the return type and trust level, and the absence of side effects. The agent has the necessary information to call the tool correctly and handle its output safely.

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 provides complete documentation for the single 'data' parameter, including type, length limits, and encoding constraints. The description itself adds no additional parameter-specific semantics, so the baseline of 3 is appropriate given the high schema 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 states a specific action ('Generate') and a specific resource ('a QR code') using the LifeStep QR API, and clarifies the return format as SVG markup. This makes the tool's purpose unmistakable and clearly distinct from the sibling tools, which inspect workbooks, look up domains, and validate email.

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 does not explicitly say when to use this tool versus alternatives, nor does it provide exclusions or conditions where another tool should be preferred. The usage context is only implied by the action of generating a QR code, with no explicit routing guidance or prerequisites.

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?

The annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description's bar is lower. It still adds meaningful context beyond the annotations: workbook content is never executed, the returned JSON is explicitly untrusted text, and the decoded size is capped at 5 MiB. No contradiction with annotations exists.

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 short sentences, each carrying distinct information: the action and purpose, the return format with a trust warning, and the size limit. The core verb-action is front-loaded; there is no filler or repetition of schema details.

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 two-parameter, read-only tool with 100% schema coverage and safety annotations, the description covers the essential runtime facts: safe inspection without execution, untrusted output, and the size bound. With no output schema present, it even discloses the return format ('original JSON as untrusted text'), leaving little an agent needs before invoking.

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 100%, so the schema already documents filename (pattern, length, no path) and content_base64 (canonical padded base64, no whitespace or data URL, byte cap). The description's mention of base64 format and the 5 MiB decoded size reinforces but does not go beyond the schema, warranting the baseline 3.

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: uploading one base64 XLSX/XLSM to the LifeStep Inspector API to inspect macros, external links, formula counts, and hidden sheets. This concrete scope clearly distinguishes it from the sibling tools (generate_qr, lookup_domain, validate_email), which serve entirely different purposes.

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 intended use case is implied through the enumerated inspection targets (macros, external links, formula counts, hidden sheets), and the 5 MiB limit implicitly excludes larger workbooks. However, there is no explicit when-to-use / when-not-to-use statement or reference to alternative tools, so the agent must infer routing from the description alone.

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 already disclose readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds valuable behavioral context: it returns the original JSON as text, warns that upstream content is untrusted data, and reiterates no writes or bulk queries. This goes beyond annotations and gives the agent meaningful operational expectations.

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 concise sentences that front-load the action, then state the output format, the trust warning, and the constraints. Every sentence carries distinct information 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 single-parameter read-only tool with rich annotations and detailed schema, the description covers the essential operational context: what it does, what it returns, the untrusted nature of the data, and the constraints against bulk or write usage. The lack of an output schema makes the explicit statement of 'original JSON as text' particularly valuable, and the description is sufficiently complete for correct invocation.

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 100%, so the baseline is 3. The tool description does not add new parameter semantics beyond the schema; it only reiterates 'one public domain,' which the schema already specifies. No extra value is provided for the domain parameter.

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 verb ('Look up'), the resource ('one public domain'), and the specific API ('LifeStep Domain Info API'). It also distinguishes itself from potential bulk or write operations with 'No bulk queries or writes,' making its scope unambiguous and differentiating it from any hypothetical alternative.

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 clearly states the tool is for a single public domain lookup and explicitly excludes bulk queries and writes, providing a clear when-not. It does not name alternative tools, but the sibling tools (generate_qr, inspect_workbook, validate_email) are unrelated, so this is not a significant gap.

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 annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint), the description adds meaningful behavioral context: no SMTP probe is sent, mailbox existence is not guaranteed, and the return is 'original JSON as untrusted text.' This communicates safety and trust implications that annotations alone do not cover.

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 deliver all essential information with zero fluff. The first sentence front-loads the primary purpose and the specific validation dimensions; the second adds critical limitations and return-type details. 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 single-parameter, read-only validation tool with rich annotations and a complete schema, the description covers all necessary invocation details: what checks are performed, what is not performed, and the return format. Nothing an agent needs to call it correctly 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?

Schema description coverage is 100%, so the schema already fully documents the email parameter including format, length, and punycode guidance. The description adds little beyond the word 'one' and 'ASCII,' which are already implicit in the schema. Baseline 3 is appropriate.

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 ('Check'), a concrete resource ('one ASCII email'), and enumerates the exact validation categories (syntax, MX, disposable provider, role account, typo suggestion). This clearly distinguishes it from sibling tools like generate_qr, inspect_workbook, and lookup_domain, none of which perform email validation.

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 states a clear use case and an explicit limitation: 'No mail or SMTP probe is sent; mailbox existence is not guaranteed.' This effectively tells an agent when not to use this tool (when confirmed mailbox existence is required). It does not name alternative tools, but the sibling set is quite distinct, so the context is sufficient.

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