capacitor-mcp

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

Annotations already cover readOnly/openWorld/destructive hints. The description adds behavioral details such as returning the page title, URL, version, and full markdown, and that anchors are ignored. 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 well-structured: purpose, usage, return value, negative usage, and alternatives are presented in a logical order. It is detailed yet concise, with no 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?

The description covers when to use, when not to use, what is returned, and how to handle version matching. It even mentions the need to match the user's package.json version, providing sufficient context for an agent to invoke the tool correctly without an output schema.

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 itself provides thorough descriptions for both parameters (url with examples and anchor note, version with enum and default). The tool description adds no extra parameter semantics beyond the schema, so the baseline score 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 tool's function: reading the full markdown of a single Capacitor documentation page. It also differentiates itself from siblings like search_docs by noting that it returns complete pages rather than snippets, and mentions the exact domains it covers and excludes.

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?

Explicit guidance is provided: use after search_docs to read full pages, do not use to find pages, and do not use for non-capacitorjs.com domains (with alternative tools named). This gives clear when-to-use and when-not-to-use instructions.

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 read-only and non-destructive nature. The description adds that it returns the 10 most recent posts and that the feed carries only the newest posts, giving some limitation context but not rich behavioral detail.

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, action-oriented, and logically structured with usage guidance and return details.

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 simple, and the description covers purpose, usage, return values, and exclusions, making it complete without an output schema.

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?

There are no parameters, so the baseline of 4 applies. The description doesn't need to add parameter semantics.

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 states it lists the 10 most recent blog posts from the Capacitor tag, and explicitly differentiates from search_docs for documentation questions.

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 when-to-use ('when the question is about what is new') and when-not-to-use ('Do not use this to answer a documentation question') with a pointer to the alternative search_docs.

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 read-only and non-destructive hints; the description adds behavioral details such as result ranking and defaults, enhancing transparency without contradicting 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 well-structured and informative, though it slightly redundantly repeats the official/community distinction. Overall, it remains concise and each sentence serves a purpose.

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 fully explains the return fields (name, description, source, maintainer, url, core, experimental) and ranking behavior, providing complete context for a listing tool without an output schema.

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 provides full descriptions for all three parameters including enums and defaults. The description adds no significant extra semantic meaning 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 clearly states the tool lists Capacitor plugins, distinguishes official and community sources, and explicitly names the sibling tool get_doc_page for reading APIs, making its purpose 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?

It explicitly states when to use the tool ('find a plugin for a native capability before writing custom native code') and when not to use it, directing to get_doc_page and the Capawesome MCP server, providing clear usage 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?

The readOnlyHint annotation already signals that the operation is read-only, so the bar is lower. The description adds useful behavioral detail: it returns page sections with specific fields (title, url, snippet, section, version) and notes that no search operators are supported, which helps set expectations. It does not contradict the annotation.

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 longer than the minimal example but every sentence adds value—purpose, usage, excluded scenarios, and output format are all covered without redundancy. It is well-structured and flows logically, though it could be slightly compressed without losing 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?

The description covers everything an agent needs: when to use, what to search, what results look like, and what to avoid. Since an output schema exists, it does not need to detail return values, but it does anyway. It also addresses version matching and section restriction, making it self-contained for correct invocation.

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 provides descriptions for all four parameters, giving 100% coverage. The description adds extra context by providing example queries and emphasizing that plain keywords work best, which goes beyond the schema. It also clarifies the effect of the version parameter indirectly by mentioning matching the user's package.json. This adds meaningful guidance.

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: searching the official Capacitor documentation by keyword. It also distinguishes itself from sibling tools by explicitly mentioning what it does not do (e.g., reading a full page, listing plugins) and by naming the sibling tools (get_doc_page, list_plugins).

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 explicit guidance on when to use this tool ('Use this first for any question about Capacitor itself') and when not to use it, providing concrete alternatives for excluded cases (e.g., using get_doc_page for reading a whole page, using the Capawesome MCP server for plugins). This is highly actionable.

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