fastdrop

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

Annotations already mark as readOnly and idempotent. Description adds that it searches actual tool lists from endpoints, not maker-supplied tags, which clarifies behavior and data source beyond 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?

Two concise sentences with purpose front-loaded. No filler words, but could clarify product/tool ambiguity. Efficient for a simple 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?

Given output schema exists and annotations provide safety hints, description adequately explains purpose and data source. Does not need to describe return values. Slight gap in clarifying scope of search.

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 description need not add detail. It mentions 'by capability' but does not describe the parameters beyond what schema provides. Baseline score 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?

States finding live FastDrop products by capability, and clarifies it searches actual tool lists, not tags. The verb 'find' and resource 'products' are clear, but the tool name is 'find_tools' which creates minor confusion. Still differentiates from siblings by specifying data source.

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?

Indirectly suggests use when you need real tool capabilities from endpoints, not tags. Does not explicitly state when to use or provide alternative tool names, but context from sibling tools and description helps. Lacks clear exclusion criteria.

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 as read-only, idempotent, and non-destructive. The description adds valuable behavioral details: it returns MCP URL, mcpVerified, last-verified timestamp (when available), and probed tool list read from endpoint (not maker-supplied tags). This enriches the agent's understanding beyond the structured 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 a single, clear sentence that efficiently conveys the tool's action and return data. It is front-loaded with the core purpose. No unnecessary words. However, it could be slightly more structured, e.g., separated into purpose and return information, but it is still 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?

Given the tool's simplicity (one required parameter, read-only, has output schema), the description is fully sufficient. It covers what the tool does, how to identify the resource (slug), and what data to expect. No omissions for this level of 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%, with the slug parameter well-described as 'Product slug from the /p/<slug> URL'. The description does not add new details about the parameter beyond what the schema provides. It mentions the return fields indirectly, but that does not enhance parameter understanding. 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 identifies the verb 'Get', the resource 'one live FastDrop product', and the identifier 'by its slug'. It distinguishes the tool from siblings like search_products and list_comments by specifying a single product retrieval. The return fields are also listed, leaving no ambiguity about the tool's purpose.

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 you have a slug and need product details. It does not explicitly state when not to use it or suggest alternatives, but the sibling tool names provide context for differentiation. A more explicit exclusion statement would warrant a 5.

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 non-destructive. The description adds beyond this: it reveals the two-level tree structure and that removed comments appear as tombstones, which is useful for agent understanding.

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: two sentences that are front-loaded with the core purpose and immediately provide valuable detail. No unnecessary words.

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 rich annotations, output schema, and clear parameter schema, the description adds necessary context (tree structure, tombstone, authentication) to make the tool fully self-explanatory.

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% description coverage for both parameters, so the description adds no additional meaning. This meets the baseline expectation.

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 it lists comments by product slug, and specifies the two-level tree structure (top-level and replies). This distinguishes it from sibling tools like list_reviews or get_product.

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 clear context: it lists comments for a live FastDrop product by slug, and notes it is unauthenticated. However, it does not explicitly state when not to use it or compare to 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 declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds value by detailing specific fields returned (MCP endpoint URL, mcpVerified, mcpAuthRequired), which is beyond basic safety traits.

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, no redundant information. Every sentence contributes meaningful detail.

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?

Description covers ranking and special fields. Output schema exists to explain return format. Could mention pagination or error handling but not required given output schema. Overall adequate.

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 both parameters (limit, window) described in the schema. The description does not add additional meaning or context beyond what the schema provides, so 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 (List), resource (live product launches), and context (ranked by votes). It differentiates from sibling tools like list_comments or list_reviews by specifying launches.

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 for viewing ranked launches but does not explicitly state when to use this tool vs alternatives like search_products or find_tools. No when-not-to-use 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 readOnlyHint, idempotentHint, and destructiveHint. Description adds that it is unauthenticated and details return data, going beyond annotations. No contradictions.

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 concise sentences with front-loaded purpose. No unnecessary words, every sentence 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?

Given rich annotations, complete schema, and output schema, the description covers essential aspects: purpose, authentication, and return data. No gaps identified.

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 covers 100% of parameters with descriptions. Description adds context about 'by its slug' but does not significantly exceed schema explanation. 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?

Description clearly states 'List reviews for a live FastDrop product by its slug' with specific verb and resource, and includes return fields. Distinguishes from siblings like list_comments and list_launches.

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?

Explicitly mentions 'Unauthenticated - available to any agent' and implies usage for reading reviews. Lacks explicit when-not-to-use but provides sufficient context given siblings are for different resources.

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?

Description adds behavioral context beyond annotations: results ranked by votes, include verification status and freshness. It also mentions 'live' products and optional x402 filtering. No contradiction with readOnlyHint, idempotentHint, etc.

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 dense sentences, front-loaded with core action, no fluff. Could slightly improve by separating filter and ranking details, but overall efficient.

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 an output schema exists, the description covers key output fields (verification, freshness) and ranking. Mentions pagination implicitly via limit. Sufficient for agent to understand tool 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 coverage is 100%, so baseline 3. Description explains query/tag matching and limits, but does not add significant new semantic detail beyond what the schema already provides (e.g., parameter names, 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 purpose: search live FastDrop products by text, tag, or both, with optional filter and ranking. It distinguishes itself from siblings like get_product (single product) and list_* (list all) by being a search tool.

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?

No guidance on when to use this tool versus siblings like find_tools or list_launches. The description implies it's for searching products, but does not specify when to prefer this over other tools.

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