Fetch products from a Product Hunt user's stack and identify who recommended each, so you can analyze their recommendations and interests.
Products in a Product Hunt user's stack with who recommended them. 1 point per returned record.
| Name | Required | Description | Default |
|---|---|---|---|
| user | Yes | Username or Product Hunt profile URL. e.g. kevin | |
| max_items | No | Max items (up to 250) |
Changes observed during successful MCP inspections.
v1.0.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so the description carries full behavioral burden. It discloses a useful cost trait ('1 point per returned record'), but says nothing about pagination, ordering, permissions, or what the stack/recommender records actually contain at a behavioral level.
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 short sentences, resource described first, cost note second, zero filler. Front-loaded and appropriately sized.
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 two-parameter read tool with no output schema, the description communicates the returned entity ('products ... with who recommended them') and a cost hint, which is most of what an agent needs. It lacks routing context against the large Product Hunt sibling set and any return-shape detail, keeping it short of a 5.
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% (user and max_items are both documented, with an example and a 250 cap), so the schema does the heavy lifting. The description adds nothing about parameter semantics beyond what the schema already states; baseline 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?
Clear specific verb-less but resource-specific statement: what the tool returns (products in a Product Hunt user's stack) plus the enrichment (who recommended them). It names a distinct resource ('stacks') that separates it from generic Product Hunt user tools, but it does not explicitly differentiate from near siblings like run_producthunt_users_collections or run_producthunt_users_upvotes.
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 statement of when to use this over alternatives. Given the dense cluster of run_producthunt_users_* siblings, an agent gets no routing guidance, only implied usage from the resource name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.