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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds useful context about what is checked (signed-in status and active account) and frames it as a diagnostic first step, going slightly 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 filler. The primary purpose is stated first, and the usage guidance is added in the second sentence without 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 a zero-parameter diagnostic tool, the description fully covers what it does, what it reveals, and when to use it. No output schema exists, but none is needed for this simple status check.

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, so there is nothing for the description to clarify beyond the empty schema. The absence of parameters makes the baseline score of 4 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 states a specific action ('check whether the server is signed in to Google') and specifies the additional detail of which account is being used. It is clearly distinct from sibling document/comment 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 explicitly says to call this tool first when other tools fail with authentication errors, giving a concrete condition for when it should be used. This is strong contextual guidance.

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 tool read-only, idempotent, and non-destructive. The description adds behavioral value by disclosing what is returned: the full reply thread, quoted text, and optional surrounding paragraph. No contradiction.

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?

One dense 19-word sentence that front-loads the verb and resource and then lists key output elements. There is 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 no output schema, the description supplies enough return-value detail (reply thread, quoted text, surrounding paragraph) while annotations and schema cover safety and parameters. It could mention error/not-found behavior or explicitly distinguish alternatives, but these are minor gaps for this simple fetch.

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 document, comment_id, and include_context with descriptions, and format has an enum/default, so schema coverage is high. The description adds little parameter-level nuance beyond restating 'by ID' and the returned thread context.

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 ('Fetch') and resource ('one comment of a Google Doc by ID') and lists what is included ('full reply thread, quoted text and surrounding paragraph'). This clearly distinguishes it from list_comments and get_comments_summary without needing the schema.

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's focus on a single ID implies targeted retrieval, and the schema clarifies the prerequisite by saying comment_id is 'as returned by list_comments.' It does not explicitly name sibling tools or state when not to use it, but the context 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?

The description adds behavioral context beyond the annotations: it explicitly states 'Reads every page of comments,' which signals that this operation may be costly or time-consuming. The annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, but the description's note about reading all pages is an additional useful disclosure. No contradictions with annotations exist.

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. The first sentence front-loads the core purpose and lists the key outputs, and the second adds a single behavioral note. It is tightly written and every phrase contributes value, making it an excellent example of conciseness.

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 summary tool with no output schema, the description covers the key return content (counts by status, participants, open comments, etc.) and the behavior (reads all pages). It does not explicitly mention the format parameter or the output format, but the format parameter with its enum is present in the schema. The annotations handle the read-only safety. Overall, the description provides sufficient context for an agent to invoke it correctly, with minor gaps like not stating the return type directly.

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 50%: the document parameter has a clear description, but format has no description beyond its enum values. The description does not elaborate on either parameter. However, the format enum (markdown/json) is self-explanatory, and the document parameter is already well-documented. Since the coverage is not high (>80%) but also not low (<50%), the baseline is 3, and the description adds no extra parameter meaning, so a 3 is justified.

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 that the tool provides an aggregate view of all comments in a Google Doc, listing specific metrics like counts by status, participant activity, and open comment details. It distinguishes itself from siblings like list_comments or get_comment by focusing on summary data rather than raw comment listings, though it does not use an explicit verb like 'get' or 'retrieve'. The resource (comments in a Google Doc) and the nature of the output are clear, so it earns a 4 rather than a 5.

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 an aggregate summary is needed rather than individual comments—but it does not explicitly mention alternatives or conditions for choosing this over list_comments or get_comment. It says 'Aggregate view' which suggests it's for high-level insights, but there is no direct 'use this when' or 'use list_comments for details' guidance. This is adequate but not explicit, so a 3 is appropriate.

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, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds valuable behavioral detail beyond annotations: it specifies that the tool returns metadata fields and plain-text content, and that it spans all tabs. This is useful context for return-value expectations, though it doesn't cover edge cases like truncation or permission failures.

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 concise sentences with no filler. The first sentence front-loads the core function and output, and the second gives a practical use case. Every word 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 read-only tool with no output schema, the description does a good job of summarizing what the agent will receive (metadata plus plain-text content) and why it's useful. It doesn't fully cover what happens when max_chars is hit or whether the content is formatted, but the schema covers the main parameter, and the core use case is clearly supported.

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%, with all three parameters already documented in the input schema. The description adds little parameter-level semantics beyond what the schema provides, e.g., it doesn't describe the interaction between max_chars and content truncation. This meets the baseline for 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 uses a specific verb ('Read') and identifies the resource ('a Google Doc') and the exact scope: metadata (title, owner, last modified) and plain-text content across all tabs. It distinguishes itself from sibling tools like list_documents and the comment-specific tools by clarifying this is about reading the document text, not listing or fetching comments.

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 'Useful to understand what the comments refer to' provides clear context for when to use this tool, especially alongside the comment-related siblings. It doesn't explicitly state when not to use it or name alternatives, but the context is strong enough for an agent to infer the intended use case.

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 cover readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is established. The description adds meaningful behavioral/return detail: every reply thread, who resolved or reopened it, and the optional surrounding paragraph, though pagination and result-shape behavior are left to the schema.

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, front-loaded with the action and the specific output contents, with no filler. The second sentence adds useful context about the tool's role on the server rather than repeating 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?

For a 7-parameter tool with 100% schema coverage, strong safety annotations, and no output schema, the description supplies the missing output-content context. It does not describe pagination or result shape, but page_token and max_results are already schema-described, leaving only a minor gap.

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 even without parameter info in the description. The description only hints at include_context via 'optionally, the surrounding paragraph,' but the schema already documents that; it adds no extra meaning for the other six parameters.

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?

States a specific verb ('List'), resource ('comments of a Google Doc'), and the scope of what is returned: author, dates, status, quoted text, replies, and who resolved/reopened. The 'full detail' framing and 'main tool' context distinguish it from get_comments_summary and get_comment without needing to inspect 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?

Calling it 'the main tool of this server' faintly implies it is the default for reading comments, but there is no explicit when-to-use or when-not-to-use guidance relative to get_comments_summary or get_comment. This is implied usage rather than clear exclusions or alternatives.

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 cover the safety profile (read-only, idempotent, non-destructive), so the description's job is to add behavioral context. It adds that shared drives are included, results are sorted newest first, and the returned fields include name, ID, owner, and last-modified date. This is meaningful beyond the annotations, though it does not mention pagination behavior explicitly.

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 short sentences with no filler. It front-loads the core action and scope, then gives returned fields/sorting, then closes with actionable guidance. 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?

The tool is a simple read-only list operation with no required parameters and no output schema. The description covers what it searches, the fields returned, the ordering, the shared-drive scope, and how to use the result IDs with other tools. Pagination is already explained by the page_token schema description, so nothing essential 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 67%, with query and page_token already documented in the schema and max_results constrained by minimum/maximum/default values. The description adds little parameter-level meaning beyond the verb "Search," so it neither compensates for gaps nor adds value beyond 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 states a specific verb and resource: "Search the user's Google Drive for Google Docs documents." It further clarifies scope by noting shared drives are included and distinguishes the tool from siblings by stating the returned fields and sort order. An agent can immediately understand this is the entry-point listing tool as opposed to get_document or list_comments.

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 usage context: it searches Drive and says "Use the returned ID with the other tools," which implies this is the discovery step before calling document or comment tools. It does not explicitly name alternatives or exclusions, but the sibling tools are distinct enough that no conflict arises.

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