Lazyweb Public Discovery

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

Annotations already mark it read-only, non-destructive, open-world, and idempotent; the description adds meaningful behavioral detail: no authentication or setup, average response time, and citation-backed output. This is exactly the kind of context that helps an agent trust and invoke it appropriately.

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, front-loaded with the most important instruction ('use this first'), and every sentence adds a distinct fact: scope, behavior, speed, and no setup required. 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?

For an 8-parameter tool with no output schema, the description covers scope, output form, performance, and authentication requirements. It could be slightly more complete by indicating what happens when no answer is found or by pointing to the sibling tools for follow-up page-level tasks, but the essentials are present.

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 explains question, user_goal, discovery_path, alternatives_considered, and optional fields. The description adds no per-parameter meaning beyond pointing at the corpus being searched, so the baseline of 3 applies.

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 action ('searches Lazyweb's complete public corpus') and result ('returns a concise, citation-backed answer'), and frames it as the primary tool for any Lazyweb question ('use this first'). It also contrasts with page-by-page browsing, helping distinguish it from the page-oriented siblings.

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 explicitly says to use this tool first for any question about Lazyweb and advises against browsing page by page, which serves as a when-not. It does not name the sibling tools (lazyweb_search, lazyweb_page_tldr) as concrete alternatives, so the guidance is clear but slightly generic.

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 mark the tool as read-only, idempotent, and non-destructive. The description adds meaningful context by stating it uses indexed public content and source links, and that non-public state is out of scope. 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?

Two sentences with no filler. The core action and resource are front-loaded, followed by useful scope and exclusion 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 simple read-only extraction tool, the description plus fully covered schema and annotations is nearly complete. It could explicitly name sibling alternatives or describe the return shape, but these are minor gaps rather than blockers.

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 individual parameters are already well documented. The tool description adds only high-level context about known-page extraction rather than new parameter-specific meaning, which matches the baseline for full 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 and resource: 'Get a compact extract of a known page in Lazyweb's public library.' It also clarifies scope by excluding signed-in workspace and private account state, which distinguishes it from broader search or ask 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 clearly indicates this tool is for known public pages and explicitly excludes private/workspace content. However, it does not name sibling tools like lazyweb_ask_anything or lazyweb_search or give explicit conditions for choosing them instead.

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, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well covered. The description adds meaningful behavioral context by specifying that the tool returns 'indexed public evidence and source links' and that the search scope includes non-Lazyweb products. This goes beyond the annotations 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 a single sentence with no filler. It front-loads the action and resource, then adds scope and return-value information. Every clause contributes useful meaning for an agent deciding whether to invoke the tool.

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 search tool with fully self-documenting schema parameters and strong annotations, the description covers the core behavior and return type. It does not explain output formatting or pagination, but there is no output schema and the description's mention of 'evidence and source links' gives sufficient context for an agent to invoke the search and interpret the result. It could be slightly more explicit about how this compares to ask_anything or page_tldr, but overall it is complete enough.

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 each of the 8 parameters has a descriptive schema entry. The tool description itself adds no parameter-level detail, but it does not need to because the input schema already explains question, user_goal, discovery_path, alternatives_considered, and the optional fields. This matches the baseline of 3 when the schema carries the parameter documentation burden.

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 ('Search'), a specific resource ('public Lazyweb library'), and the scope of content ('products, companies, flows, research and comparisons'). It also clarifies an important boundary: the library includes pages about products other than Lazyweb. This clearly distinguishes the tool from the sibling tools by describing what it searches and what it returns.

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 when to use this tool: when the agent wants to search the public Lazyweb library for indexed pages and evidence. However, it does not explicitly mention when not to use it or name alternatives like lazyweb_ask_anything or lazyweb_page_tldr. The usage context is present but left to inference rather than stated.

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