Mark a notification (or all unread) read. Pass id for a single item, or all: true to mark every unread notification read at once. Idempotent.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Notification id to mark read | |
| all | No | Mark every unread notification read |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already signal idempotentHint=true, readOnlyHint=false, and destructiveHint=false, so the baseline is fairly high. The description adds useful bulk behavior shows the full scope of the mutation ('mark every unread notification read at once') and restates idempotency, while agreeing fully with 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?
Two sentences with zero filler. The primary action is front-loaded, the two call variants are clearly separated, and the idempotency note is economical and worthwhile.
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, idempotent mutation with annotations and no output schema, the description covers all essential decisions: what the tool does, how to target one item, how to target all unread, and that repeated calls are safe. Slight extra detail about the behavior when both `id` and `all` are supplied would be the only remaining improvement, but it is not necessary for a confident call.
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 `id` and `all`. The description adds meaning by framing the two parameters as alternatives ('Pass id ..., or all: true'), which communicates mutual exclusivity and resolves the ambiguity of whether both can be used together.
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 opens with a specific verb and resource ('Mark a notification ... read') and immediately disambiguates the two modes: single item via `id` or all unread via `all: true`. It clearly distinguishes itself from its read-oriented siblings like `list_notifications` and `get_unread_count` by indicating a state-changing action.
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 usage guidance, walking the agent through the two valid call patterns: supply `id` for one notification, set `all: true` to mark everything read. It does not explicitly name alternative sibling tools for when not to use this tool, but the conditional branches are clear and operationally useful.
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.
