Fetch a Cobalt Capture review by its share link or slug. Returns the reviewer's notes as text AND each annotated screenshot as an image, so you can see exactly what was marked and what to change.
| Name | Required | Description | Default |
|---|---|---|---|
| review | Yes | A Cobalt review URL (https://cobaltcapture.com/r/<slug> or /s/<slug>) or just the slug. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already signals this is a safe read, and the description adds meaningful behavioral context by disclosing the return payload: reviewer notes as text and each annotated screenshot as an image. This goes beyond the annotation by telling agents what to expect from the response.
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 tight sentences: the first states what the tool fetches and how to address it, the second states what the caller gets and why that matters. No wasted words, and the key retrieval mechanism 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 read-only tool with one fully documented parameter, the description provides enough to call it correctly: the input form, the output content, and the purpose. It omits not-found behavior or response format details, but the absence of an output schema is reasonably compensated by the natural-language return description.
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% and already documents the 'review' parameter as either a URL or a slug. The description's phrase 'share link or slug' largely repeats the schema without adding new detail like examples, validation behavior, or how to extract the slug. 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?
The description uses a specific verb ('Fetch'), identifies the resource ('a Cobalt Capture review'), and explains the input form ('share link or slug'). It also distinguishes GET-style review retrieval from siblings like create_review, update_review, and email_review by stating what it returns: notes plus annotated screenshots.
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?
It is clear this tool is for reading an existing review via its share link or slug, and the return description makes its use case apparent. However, it does not explicitly contrast with create_review, update_review, or email_review, so the when-not-to-use guidance is implied rather than stated.
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.
Each tool targets a distinct resource and action: reviews (create/get/update/email/add content), inboxes (create/check), and playbooks (get). No two tools overlap in purpose, and descriptions reinforce the boundaries.
All tool names follow a consistent verb_noun snake_case pattern (add_, check_, create_, email_, get_, update_). The verbs clearly indicate the operation and the nouns indicate the resource, making the API predictable.
Nine tools is well-scoped for the server's purpose: covering review lifecycle, inbox support, and playbook retrieval without redundancy. Each tool earns its place in the QA/capture workflow.
The tool surface covers the full review lifecycle (create, append, retrieve, update, email) plus supportive inbox and playbook operations. Minor gaps like no explicit delete or list operations exist, but auto-expiry and share-link retrieval mitigate them.