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worldnine

Scrapbox Cosense MCP Server

by worldnine

get_page

Retrieve page content and linked pages from Scrapbox projects on cosense, returning titles and descriptions in plain text format.

Instructions

Get a page from Scrapbox project on cosense (scrapbox). Returns page content and its linked pages. Page content includes title and description in plain text format. Uses my-cosense-project project as default if projectName is not specified.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageTitleYesTitle of the page
projectNameNoTarget project name. If not specified, defaults to 'my-cosense-project'.
Behavior3/5

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.

Conciseness4/5

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.

Completeness3/5

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.

Parameters3/5

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.

Purpose4/5

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.

Usage Guidelines3/5

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.

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