webanalyzer

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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds useful operational transparency: deterministic 290+ checks, free/no auth, daily quota, and unsupported page types. No contradiction with 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?

The main action and return value are front-loaded in the first sentence, followed by concise constraints in the second. No filler or repeated schema 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?

With one parameter and no output schema, the description fully informs the agent what the tool returns and under what conditions it works. Minor omissions like exact error/rate-limit behavior keep it from a 5.

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 covers the single URL parameter at 100%. The description adds meaningful constraints beyond the schema by specifying public URLs only, excluding localhost and login-gated pages, and implying an http(s) full URL format.

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?

Clearly identifies the action ('analyze a public web page') and the exact output: 0-100 quality score, letter grade, dimensions, and top issues. It does not explicitly compare itself to get_analysis or get_leaderboard, but its command semantics make it distinct enough.

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?

Gives strong contextual guidance: public pages only, no auth, free, and a 3-analysis daily limit. It also explicitly excludes localhost and login-protected pages. It does not name sibling tools as alternatives for retrieving prior results or leaderboards, so it stops short of a 5.

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 declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds value by specifying what the response contains (score, grade, per-dimension scores, top issues) and where valid ids come from, giving the agent useful behavioral context beyond 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?

The description is two sentences with no wasted words. It front-loads the action and resource, then efficiently covers what the response includes and where the id comes from. 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 simple one-parameter fetch with no output schema, the description is complete: it states the input provenance, the output content, and the operation type. An agent needs no additional information to invoke the 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?

Schema description coverage is 100%, and the schema already documents the id parameter thoroughly, including its return source and URL relationship. The description repeats and slightly reinforces this information but does not add meaningful new semantics 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 uses a specific verb ('Fetch') with a clear resource ('stored analysis') and a key identifier ('analysis id'), and it lists the returned contents (score, grade, per-dimension scores, top issues). It is clearly distinguished from siblings: analyze_website creates runs, get_analysis fetches a previous run's result, and get_leaderboard serves a different purpose.

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 when to use this tool: after a previous analyze_website run, when you have an id from that run's results or from a report URL. It does not explicitly name alternatives or say when not to use it, but the context is unambiguous enough for an agent to select this tool 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?

Annotations already declare the operation is read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond annotations by specifying that results are public, sorted best-first, and include score fields, which covers the main return semantics an agent needs.

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, focused sentence that immediately states the resource and key output characteristics. Every element earns its place with no filler or redundant 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?

For a simple read-only leaderboard tool with one optional parameter and no nested objects, the description plus annotations and schema are fully sufficient. It communicates what the tool returns, the ordering, and the field composition, so an agent can invoke it correctly without missing information.

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 has 100% description coverage for the single optional 'limit' parameter, including constraints and default value. The tool description does not add further parameter detail, but none is needed since the schema already fully documents it; 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 clearly states the tool returns the public WebAnalyzer leaderboard, with specific details on what is included (website name, URL, 0-100 score) and ordering (best first). This distinguishes it from sibling tools that analyze or retrieve individual website analyses.

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 use when the agent needs a high-level public ranking of analyzed websites rather than an individual site's analysis. It doesn't explicitly name alternatives or exclusions, but the 'public leaderboard' framing gives clear context for when it is appropriate.

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