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

No annotations are provided, so the description must carry the behavioral details. It discloses that it uses the WebSocket API, returns the page creation URL without opening a browser, and mentions the createActually flag behavior. It doesn't address error handling, idempotency, or permissions, which are relevant for a write operation. Overall, it provides some behavioral insight but leaves gaps.

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 sentences and front-loaded with the core action and outcome. It packs essential information about return behavior and defaults without redundancy. Every sentence adds value; no fluff.

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 5 parameters, no output schema, and no annotations, the description covers the key aspects: creation, default project, body format, and the createActually flag. It does not mention what happens if the page already exists or error conditions, but for a straightforward create tool that's acceptable. The description is complete enough for typical agent use, with the main gaps being edge cases.

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 each parameter already has a description. The description adds a useful note about not duplicating the title in the body ('Avoid duplicating the title in the body since it's automatically displayed at the top') and clarifies the default behavior for format and projectName. This exceeds what the schema states, but not significantly, so a 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 clearly states the action: 'Create a new page in Scrapbox project on cosense (scrapbox).' It specifies the verb 'create' and the resource 'new page', and distinguishes itself from siblings like search_pages, get_page, and edit_lines by focusing on creation. The phrase 'returns the page creation URL without opening browser' adds clarity on the outcome.

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 mentions the default project behavior ('Uses my-cosense-project as default if projectName is not specified') and the body format options, giving context for usage. However, it does not explicitly state when to use this tool over siblings (e.g., when to prefer create_page vs edit_lines), though the create-vs-edit distinction is implicit. No exclusions or when-not-to-use guidance is given, but for a creation tool, this is adequate.

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?

Since no annotations are provided, the description carries full burden. It discloses matching semantics, block removal with newlines, default first-match behavior, matchAll option, refusal to delete title line, error handling for no match, authentication requirement (COSENSE_SID), and default project. This is highly transparent.

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, well-organized paragraph that front-loads the primary action and then details edge cases and constraints. Every sentence conveys necessary information without fluff, making it appropriately sized for the complexity.

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?

As a mutation tool with no output schema and no annotations, the description covers all critical aspects: operation semantics, edge cases (title line, multiple matches, block removal), error conditions, authentication, and defaults. It is complete for the tool's complexity.

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 is thorough, but the description adds substantial value: exact-match and case-sensitive semantics, newline as block, atomicity for block matches, title-line protection, and default project behavior. This goes beyond the schema's descriptions.

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 deletes lines from a Scrapbox page and matches by exact text. It also differentiates from delete_page for deleting the title line, distinguishing it from 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?

Provides explicit guidance on when to use (delete lines) and when not (use delete_page for deleting the page/title). Also mentions default project behavior, though it doesn't contrast with edit_lines or insert_lines, but the core use case is clear.

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 fully discloses behavior: exact, case-sensitive matching; contiguous newline-block replacement; non-overlapping matchAll; error on missing match; and COSENSE_SID requirement. This gives an agent strong information about side effects and failure modes.

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, front-loaded, and has no filler. Every sentence adds a meaningful behavior or default, while keeping the total length reasonable for a six-parameter 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 mutation tool with no output schema and no annotations, the description is complete: it covers purpose, matching semantics, default behavior, multi-line replacement, project fallback, auth, and error conditions. This gives an agent everything needed to select and invoke the tool effectively.

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%, and the schema already explains targetLineText, newText, format, matchAll, and projectName. The description adds only marginal context beyond the schema, such as 'any n lines can be replaced with m lines' and the no-match error, but not enough to move far beyond the schema baseline.

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?

Description opens with 'Replace one or more lines in a Scrapbox page on cosense (scrapbox)', a specific verb and resource. It clearly frames edit_lines as replacement behavior, distinguishing it from insert_lines and delete_lines.

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 context: exact-text matching, block replacement, first-match default, matchAll option, no-match errors, and auth requirement. It does not explicitly name sibling tools as alternatives or exclusions, but it is easy for an agent to infer when replacement 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?

No annotations are provided, so the description carries the full burden. It discloses key behaviors: it returns 'page content and its linked pages' and specifies the format ('plain text format'). However, it misses details like error handling (e.g., what happens if the page doesn't exist), performance aspects, or authentication needs, which are important for a read operation without 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 appropriately sized with three sentences that are front-loaded: the first states the purpose, the second details returns, and the third covers defaults. There is no wasted text, but it could be slightly more structured (e.g., bullet points for returns) without losing 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?

Given no annotations and no output schema, the description partially compensates by explaining return values ('page content and its linked pages') and format. However, for a tool with two parameters and no structured output, it lacks completeness in areas like error cases, pagination, or example usage, leaving gaps for an AI agent to infer behavior.

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 parameters fully. The description adds minimal value beyond the schema by reiterating the default for 'projectName' ('my-cosense-project'), but does not provide additional context like examples or constraints. 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 clearly states the tool's purpose: 'Get a page from Scrapbox project on cosense (scrapbox).' It specifies the verb ('Get') and resource ('page'), and distinguishes it from siblings like 'create_page' (creation) and 'list_pages' (listing). However, it doesn't explicitly differentiate from 'get_page_url' (which might retrieve a URL rather than content), leaving some ambiguity.

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 usage by stating it 'Uses my-cosense-project project as default if projectName is not specified,' which provides context for when to omit a parameter. However, it lacks explicit guidance on when to use this tool versus alternatives like 'search_pages' or 'get_page_url,' and does not mention prerequisites or exclusions, leaving usage somewhat inferred.

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 of behavioral disclosure. It adds useful context: the tool generates a URL without browser interaction and has a default project. However, it does not cover potential errors (e.g., if the page doesn't exist), rate limits, authentication needs, or the exact URL format, leaving gaps in behavioral transparency for a tool with no annotation support.

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 concise and well-structured, consisting of two sentences that efficiently convey the tool's purpose, behavior, and default parameter. Every sentence adds value: the first defines the action and context, and the second clarifies the default project and non-browser behavior, with no redundant or wasted 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?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is partially complete. It covers the core functionality and default behavior adequately, but lacks details on error handling, return format (beyond 'direct URL'), and differentiation from siblings. Without annotations or output schema, more context would improve completeness for safe agent use.

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 clear descriptions for both parameters in the input schema. The description adds marginal value by reiterating the default project behavior for 'projectName,' but does not provide additional semantic context beyond what the schema already documents, such as examples or constraints on the 'title' parameter. Baseline 3 is appropriate given 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 clearly states the tool's purpose: 'Generate URL for a page in Scrapbox project on cosense (scrapbox).' It specifies the verb ('Generate URL'), resource ('a page'), and platform context ('Scrapbox project on cosense'). However, it does not explicitly differentiate from sibling tools like 'get_page' (which likely retrieves page content rather than just the URL), leaving room for improvement.

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 provides some usage context by mentioning the default project ('my-cosense-project') and that it 'Returns the direct URL... without opening it in browser,' which implies a non-interactive use case. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_page' or 'list_pages,' and does not specify prerequisites or exclusions, relying on implied understanding.

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 explicitly states authentication requirements (COSENSE_SID) and the default project behavior. It also discloses that the tool returns full content and uses AI-optimized formatting. While it does not explicitly state read-only or side effects, the nature of 'get context' is clearly a read operation, and no annotations exist to carry that burden. It adds meaningful behavioral context without contradicting anything.

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: it states the purpose, the return value, the use case, authentication, and a default behavior in four sentences with no filler or redundancy. It is well-structured for quick 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?

The tool is relatively complex (returns target page and linked pages with full contents) and has no output schema, but the description covers the key points: what is returned (page + linked pages, hop counts), the format (AI-optimized), the required auth, and the default project. This is sufficient for an agent to call it appropriately.

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 has 100% coverage for all three parameters. The description repeats the default projectName behavior and mentions hop counts but adds no additional detail beyond what the schema already provides. Baseline 3 is appropriate since the schema fully documents parameters, though the description could have clarified the return format structure slightly more.

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 action: 'Get smart context for a page' on cosense. It specifies the resource (page) and the scope (linked pages 1-hop or 2-hop) and distinguishes itself from sibling tools like get_page or search_pages by emphasizing the AI-optimized format and related-knowledge context.

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 indicates this tool is useful for understanding context and related knowledge around a topic, which gives a clear usage context. It does not explicitly state when not to use it or mention alternatives like get_page, but the context is clear enough and no misleading 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?

With no annotations provided, the description carries the full burden. It discloses the append fallback and default project behavior, adding useful context. However, it does not mention what happens if the page does not exist, how duplicate line matches are handled, or any permission/error conditions. This is adequate but not exhaustive.

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, succinct, and front-loaded with the core function. No unnecessary wording or repetition. Every word contributes to understanding 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?

The description handles the core insert behavior and fallback logic. It does not cover edge cases like missing pages or ambiguous target lines, but given the schema already documents all parameters and there is no output schema, it is reasonably complete for the tool's complexity.

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 description adds minimal value beyond what the schema already states. It repeats the default project and append behavior, which are also in the schema. No additional parameter insights are provided, so 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 action (insert text after a specified line) and resource (Scrapbox page on cosense). It distinguishes from siblings like edit_lines and delete_lines by focusing on insertion. The verb is specific and the target is unambiguous.

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 the tool: when you need to insert new text after a specific line, with a fallback to appending if not found. It does not explicitly mention alternatives or when not to use it, but the wording provides clear context for typical usage.

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 of behavioral disclosure. It does well by describing the return format ('Returns page metadata and first 5 lines of content'), pagination capability (implied through 'skip' parameter), and default project behavior. However, it doesn't mention rate limits, authentication requirements, or error conditions that would be helpful for a read operation.

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 appropriately sized and front-loaded with the core purpose in the first sentence. Each subsequent sentence adds valuable information about usage, return values, sorting options, and sibling differentiation. There's minimal redundancy, though the sorting methods list could be slightly more concise.

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 listing tool with no output schema, the description provides good contextual completeness by explaining what's returned, how to use it versus alternatives, and default behaviors. It covers the essential aspects an agent needs, though additional details about response format structure or error handling would make it more complete.

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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds some value by listing all sorting methods and explaining the default project behavior, but doesn't provide additional semantic context beyond what's in the schema descriptions. This meets the baseline expectation when schema coverage is high.

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's purpose with specific verbs ('browse and list pages') and resource ('from Scrapbox project on cosense'), distinguishing it from sibling tools by explicitly contrasting with search_pages. It provides concrete details about what the tool does, including the scope of returned data (page metadata and first 5 lines of content).

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 states when to use this tool ('to discover pages by recency, popularity, or alphabetically') and when not to use it ('Different from search_pages which finds content by keywords'), providing clear alternatives. It also includes practical guidance about default project behavior, making it easy for an agent to choose between this tool and its sibling.

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 of behavioral disclosure and does so effectively. It reveals important behavioral traits: result limitation ('Limited to 100 results maximum'), search syntax capabilities ('Supports basic search...'), and default project behavior. However, it doesn't mention potential error conditions, authentication requirements, or rate limits, which prevents a perfect score.

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 efficiently structured and front-loaded with the core purpose. Every sentence adds value: purpose statement, usage guidance, return format, limitations, search syntax, sibling differentiation, and default behavior. There's no wasted text, and information is presented in a logical flow.

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 search tool with 2 parameters, 100% schema coverage, and no output schema, the description provides substantial context about behavior, limitations, and usage. It explains what the tool returns ('Returns matching pages with highlighted search terms and content snippets') and search capabilities. The main gap is lack of output format details, which would be helpful given no output schema exists.

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?

With 100% schema description coverage, the baseline is 3, but the description adds meaningful context beyond the schema. It explains the default project behavior ('Uses my-cosense-project project as default if projectName is not specified') and provides search syntax examples that help interpret the query parameter. This adds practical value for parameter understanding.

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's purpose with specific verb ('Search for content') and resource ('within pages in Scrapbox project'), and explicitly distinguishes it from sibling tool list_pages ('Different from list_pages which browses pages by metadata'). This provides excellent clarity about what this tool does and how it differs from alternatives.

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 provides explicit guidance on when to use this tool ('Use this tool to find pages containing specific keywords or phrases') and when to use alternatives ('Different from list_pages which browses pages by metadata'). It also specifies the default project behavior, giving clear context for usage decisions.

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