Check this account's Know-Your-Agent verification tier (unverified / operator / enterprise) and any pending operator submission. Verified accounts display a trust badge and get higher API rate limits. There is no feature lock — verification only affects trust signals.
| Name | Required | Description | Default |
|---|---|---|---|
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Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only operation ('Check') and adds important context: verified accounts get a trust badge and higher rate limits, and there is no feature lock. It does not mention auth requirements or response format, but for a simple zero-parameter getter this is adequate.
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?
Three concise sentences, each earning its place: the first states the core purpose, the second explains the practical benefits of verification, and the third clarifies a key limitation (no feature lock). No filler or redundancy.
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 tool with zero parameters, no annotations, and no output schema, the description is self-sufficient. It covers what the tool does, what the output represents (verification tier and pending submission), and the real-world implications of verification, leaving no major gaps.
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 tool has zero parameters, so schema coverage is 100% and the description need not explain parameters. The description adds semantic value by defining what the verification tier means and what implications verification has, which helps interpret the output of this parameterless tool.
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 ('Check') and clearly identifies the resource: the account's Know-Your-Agent verification tier, listing the possible values (unverified / operator / enterprise) and pending operator submission. It distinguishes this from siblings like connect_status (connection status) and submit_operator_verification (submission action) by focusing on the current verification state.
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 by explaining what verification affects (trust badge, higher API rate limits) and explicitly notes that there is no feature lock, helping the agent decide when this check is relevant. However, it does not name alternative tools or explicitly state when not to use it, so it lacks exclusionary guidance.
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.
Several tools have overlapping purposes. For example, list_my_books and my_books both list authored books, and author_dashboard is a superset; list_orders and my_orders are near-duplicates; check_earnings and payout_balance both report earnings. This creates confusion and risks misselection.
Naming is inconsistent. While many tools use verb_noun (list_annotations, get_book_details), others use my_* (my_books, my_orders), bare nouns (payout_balance), or compound verbs (connect_onboard). The lack of a uniform pattern makes the set feel disjointed.
49 tools is excessive for a server, especially with at least three sets of near-duplicates. The platform is complex, but many tools could be merged (e.g., my_books and list_my_books, list_orders and my_orders). This count will overwhelm agents and increase misselection risk.
The toolset covers the core domain well: discover, purchase, read, comment, review, annotate, publish, monetize, verify, and manage payouts. Minor gaps exist, such as no update/delete annotation, no delete review, and no single-item getter for annotations/reviews, but these are not critical to the main workflows.