Social & Content MCP Server

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

Annotations already indicate readOnlyHint and openWorldHint, signaling a safe, non-destructive operation. The description adds behavioral context by listing the exact data returned (name, price, rating, etc.) and specifying the search scope (title or keyword). This goes beyond the annotations and gives the agent a clear expectation of output without needing an output 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?

The description is two sentences long and front-loaded with the primary action. The first sentence states what the tool does and returns, and the second gives concrete use cases. Every sentence earns its place with no redundant or vague 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?

With only two parameters and no output schema, the description carries the burden of explaining the return format, which it does by listing all returned fields. It also provides enough usage context for an agent to decide when to invoke it. Minor gaps like error handling or no-results behavior exist, but they are not critical for a read-only search tool.

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 provides descriptions for both parameters ('query' and 'max_results') with 100% coverage. The description reinforces these by mentioning 'title or keyword' and the default result count, but it does not add substantially new semantics beyond what the schema already defines. Baseline 3 is appropriate given the 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 ('Search') and resource ('Steam game platform'), clearly identifying what the tool does. It also lists the return fields, making the purpose unambiguous. Sibling tools are all search tools for different domains, so this is effectively distinguished by its target platform.

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 the tool: 'Use for game discovery, price monitoring, or review research before purchase.' This provides clear context but does not mention exclusions or alternatives. Since the tool's domain (Steam games) is distinct from siblings, the lack of explicit alternatives is not a significant gap.

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 establish readOnlyHint=true, and the description adds useful behavioral detail by enumerating the return fields (title, author, read time, publication date, tags, direct link). This is valuable given no output schema. It doesn't mention pagination or rate limits, but these are not critical for a read-only search.

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, front-loaded with the core action and output summary, followed by relevant use cases. No wasted words or redundant 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 simple search tool with full schema coverage and annotations, the description covers the essential aspects: purpose, return format, and use cases. It could mention pagination or result limits, but the schema default for max_results mitigates that. Overall, it's complete enough for an agent to use 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% with detailed descriptions for both query and max_results, so the description doesn't need to compensate. The description itself adds no additional parameter insight, such as how max_results affects output, but the baseline of 3 is appropriate given the 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 verb 'Search' and the resource 'dev.to platform', specifying it targets developer articles, tutorials, and technical posts. This effectively differentiates it from sibling tools like search_podcasts and search_events.

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 a direct 'Use for' clause listing appropriate scenarios: learning dev topics, finding tutorials, and staying updated on community trends. It doesn't explicitly mention when not to use, but the platform-specific scope gives implicit guidance relative to siblings.

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 and openWorldHint=true. The description adds the list of returned fields, but no deeper behavioral context like rate limits or pagination. This is acceptable given the annotation coverage, but not especially rich.

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 concise sentences: purpose, output fields, and use cases. No fluff, and the most important information is front-loaded.

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 search tool with no output schema, the description lists the returned fields and use cases, providing sufficient context. It doesn't cover pagination or ordering, but these are not critical for basic event discovery.

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's mention of 'topic and location' simply echoes the schema without adding new semantic meaning.

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 searches Eventbrite for events 'by topic and location', with a specific verb and resource. It distinguishes itself from sibling tools which target Steam games, Dev.to articles, and podcasts.

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 clear use cases: 'event discovery, community involvement, or entertainment planning'. Does not explicitly mention exclusions or alternatives, but siblings are different domains, making the intended usage 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?

The annotations already declare readOnlyHint=true and openWorldHint=true, so the safe, non-mutating nature is covered. The description adds the return fields (episode title, podcast name, etc.) but does not provide deeper behavioral context such as result ordering, pagination, or external API dependencies.

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: the first states the action and output, the second lists use cases. It is compact, front-loaded, and every word adds value.

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 search tool with annotations and full schema coverage, the description provides all essential information: what is searched, what is returned, and when to use it. It lacks only minor details like result limits or sorting, which are not critical for this simple tool.

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 provides 100% coverage with clear descriptions for both 'query' and 'max_results'. The description does not add significant parameter-level meaning beyond what the schema already states, 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 clearly states the tool's function: 'Search podcast directories for episodes matching topics or keywords.' It specifies the resource (podcast directories) and the output (episode metadata), and the domain distinguishes it from sibling tools like search_devto and search_events.

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 use cases: 'for podcast discovery, topic research, or building listening playlists.' This gives clear guidance on when to use the tool, though it does not explicitly mention alternatives or when not to use it.

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