Submit a review for an AI tool. Reviews queue for admin moderation before they count toward the tool's average rating.
| Name | Required | Description | Default |
|---|---|---|---|
| rating | Yes | Rating 1-5 | |
| body_md | Yes | Review body in Markdown | |
| tool_slug | Yes | AI tool slug to review |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The key behavioral trait is disclosed: reviews are queued for admin moderation before affecting the average rating. This adds meaningful context beyond the annotations, which only provide generic read/write/idempotency hints. It stops short of covering side effects such as duplicate submissions or update behavior.
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, front-loaded with the main action and followed by the one behavioral caveat that matters. There is no wasted text and the structure is easy to parse quickly.
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 create-like tool, the description combines with the full parameter schema to provide sufficient context. The moderation delay is the most important operational behavior and it is covered. It could go further by mentioning what the caller receives after submission, but this is not a major gap.
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 all three parameters. The description adds no extra parameter-level meaning, which is acceptable but not above the baseline.
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 a specific action ('Submit a review') and resource ('for an AI tool'). It also adds a distinguishing detail about admin moderation, making it easy to differentiate from generic siblings like submit_post or declare_tool_usage.
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 no explicit guidance on when to use this tool versus alternatives, and it does not mention exclusions or prerequisites. The purpose is inferable, but the description does not actively help route the agent compared to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools clearly target distinct resources and actions, but there is some overlap: get_profile and get_my_earnings both expose balance/cap information, and list_my_profiles could be confused with get_profile. The descriptions are generally clear enough to avoid serious misselection.
Every tool name follows a consistent snake_case verb_noun pattern: get_product, list_campaigns, submit_post, update_profile, etc. The verbs match the intended actions, and there are no mixed naming conventions or vague style deviations.
Twenty tools is slightly heavy, but the count is reasonable for the scope: the server covers products, campaigns, posts, earnings, profiles, notifications, asset uploads, and AI tool usage/reviews. Each tool serves a recognizable purpose, so the size feels like breadth rather than redundancy.
Core workflows are present—search products, get campaigns, apply, generate tracking links, submit posts, view earnings, manage notifications—but there are notable gaps. There is no way to list past posts or retrieve a post_id except from submit_post, no list of campaign applications, and no tool discovery endpoint for the AI tool slugs used by declare_tool_usage and write_tool_review.
