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

There are no annotations, so the description carries the full burden of behavioral disclosure. 'Check' clearly implies a read-only, non-mutating operation, and the description discloses what is inspected. However, it does not describe the return behavior, such as whether it reports a pass/fail list or throws on mixed content, which would add 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 front-loaded sentence that immediately states the purpose and uses a compact list of concrete examples. Every phrase earns its place, and the examples make the scope vivid without 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?

Given only one fully documented parameter and no output schema, the description is largely complete for selecting and invoking the tool. It clearly defines what the tool checks, though it stops short of describing the result format, which is a minor gap in the absence of an output schema.

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%, so the schema already fully documents the url parameter, including acceptable values like a live URL, preview deployment, or localhost. The description adds no additional parameter semantics beyond what the schema provides, matching the baseline of 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 ('Check') and a clearly scoped resource ('the things that get forgotten at launch'), then enumerates concrete examples such as the Vite favicon, missing meta description, and robots.txt. This itemized scope distinguishes it from sibling tools like check_security_headers or check_routes without needing to name them.

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 phrase 'at launch' gives clear contextual timing for when this tool is relevant, and the list of checks implies this is the go-to tool for common launch oversights. It does not explicitly name alternatives or say when not to use it, but the context is strong enough to route an agent correctly.

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 full behavioral burden. It discloses that the tool fetches the URL, loads og:image, verifies reachability, raster format, approximate dimensions, and platform size limits, and returns the image. This goes beyond a generic 'checks the link' and gives the agent a clear picture of what happens and what the output is.

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: primary purpose first, then the specific checks performed, then the output. Every sentence contributes useful information and there is 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 tool with no output schema, the description explains the return value ('Returns the image so you can see it') and the core behavior well. It does not mention failure modes or error handling, but the information provided is sufficient for an agent to invoke the tool correctly and interpret its primary result.

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% and the 'url' parameter is already well documented in the schema, including live URLs, preview deployments, and localhost. The description adds only general context ('on a URL') without adding parameter-level meaning beyond the schema, so the baseline of 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 names a specific verb ('Check') and a specific resource ('Open Graph and Twitter card tags on a URL'), then adds concrete detail about rendering on named platforms. This clearly distinguishes it from sibling tools like check_security_headers and check_routes without needing to open their 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 makes the usage context clear: use this when you need to inspect social sharing tags or preview how a link appears on LinkedIn, X, Slack, iMessage, and Discord. It does not explicitly state when not to use it or name alternatives, but the platform-specific preview behavior is sufficient contextual guidance 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?

With no annotations, the description carries the behavioral burden. It discloses that the tool opens links, detects SPA refresh failures, names host-specific fixes, and validates 404 behavior. This is meaningful beyond what the schema shows, though it does not detail output formatting or side effects.

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 dense but efficient, front-loading the core purpose in the opening sentence and adding valuable capabilities without fluff. Every clause contributes useful 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 two-parameter tool with fully documented schema and no output schema, the description gives enough context for an agent to select and invoke it correctly. It could more explicitly state what output format to expect, but the behavioral purpose is well covered.

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 description does not add parameter-specific detail beyond the schema, which already explains URL, live/preview/local usage, and optional extra paths for client-rendered apps.

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 specific verbs and objects: it opens internal links directly, catches single-page-app 404s, names host-specific fixes, and checks that made-up URLs return real 404s. This clearly distinguishes check_routes from generic link/preview-related sibling tools.

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 strong context: use this when needing to verify that internal routes survive refresh, bookmarks, or shared links, especially for SPAs. It does not explicitly name alternatives or when-not-to-use scenarios, but the use case is clear enough.

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 behavioral burden. It clarifies that the tool performs multiple checks and returns the header to add for each, which is useful. But it does not disclose whether it makes live network requests, whether it is read-only, or what happens when a URL is unreachable or returns non-HTTP responses.

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 one tight, front-loaded sentence that lists the checks and the output nature ('each with the header to add') without any filler. Every part 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 tool with no output schema, the description is largely complete: it names the input, the full set of checks, and the nature of the output. It could be more explicit about the result format or failure behavior, but those are minor gaps 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 input schema already documents the single url parameter at 100% coverage, including examples like localhost dev servers. The description adds little beyond 'on a URL', so the baseline of 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') and a precise resource/scope: security headers on a URL, enumerating HTTPS, redirect, HSTS, nosniff, clickjacking, CSP, Referrer-Policy, and X-Powered-By. It also notes the output includes the header to add, which distinguishes it clearly from sibling checks like check_routes or check_link_preview.

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 is implied: call this tool when you need to evaluate a URL's security headers and get recommended remediation headers. However, it does not explicitly state when to prefer this over check_basics or other sibling tools, nor does it mention any exclusions 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?

With no annotations provided, the description carries the full burden, and it does well: it discloses what the tool checks, the return artifacts (findings with fixes, platform card mockups, preview image), and the broad execution scope. It does not mention potential side effects like external fetches or rate limits, but the behavior is a read-only audit and is well described.

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 dense but organized: it opens with the general purpose, follows with a colon-delimited list of checks, then covers return values and usage timing. There is minimal filler, though the single long sentence could arguably be broken up for easier scanning.

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 complexity and lack of an output schema, the description covers the check categories, return format, and practical use cases. The optional paths parameter is only documented in the schema, but that is acceptable since the schema already provides examples and constraints.

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 both url and paths with examples and constraints. The description reinforces the live/preview/localhost use cases but adds little parameter meaning beyond what the schema provides, which matches 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 clear verb-resource pair ('Run every check on a URL') and lists the concrete coverage areas: link previews, 404 sub-pages, noindex/robots.txt, titles/favicons, security headers, and redirects. This makes it easy to distinguish from the narrower sibling tools like check_security_headers or check_link_preview.

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 positive triggers: 'Use it after deploying, before posting a link, or on localhost before pushing.' It does not explicitly say when NOT to use it or name the sibling alternatives, but the 'every check' framing makes the intended all-in-one context clear.

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