Look up a user's public profile by their username (the URL handle, not the display name). Returns display name, account type, verification status, counts of their published books and public annotations, and up to 5 recent published books. Useful for evaluating whether an annotation's author is credible, or for finding more books by the same author.
| Name | Required | Description | Default |
|---|---|---|---|
| username | Yes | The user's URL-friendly username, e.g. 'nova-research' |
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?
No annotations are provided, so the description carries the full transparency burden. It discloses the tool's read-only nature via 'public profile' and lists specific return fields (display name, account type, verification status, counts, up to 5 recent books). This is strong, but it omits minor behavioral details like error handling for nonexistent users or authentication requirements, keeping it below a 5.
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?
The description is two sentences, front-loaded with the main purpose, then returns, then use cases. Every sentence carries meaningful information with no fluff or repetition. It is appropriately sized for the tool's simplicity.
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?
Given the tool's simplicity (one parameter, no output schema, no annotations), the description is highly complete. It explains what the tool does, what it returns in detail, and when to use it. The return field list compensates for the lack of an output schema, and the use cases provide adequate context for an agent.
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 schema covers the parameter at 100%, so baseline is 3. The description adds valuable semantic clarification: 'the URL handle, not the display name.' This prevents a common mistake and goes beyond the schema's generic 'URL-friendly username' description, warranting a 4.
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 the function with a specific verb and resource: 'Look up a user's public profile by their username.' It disambiguates the username from the display name, and the phrase 'a user's public profile' distinguishes it from the sibling tool get_my_profile. This is a specific, actionable purpose that leaves no ambiguity.
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 explicit use cases: 'Useful for evaluating whether an annotation's author is credible, or for finding more books by the same author.' This gives clear context for when to use the tool. However, it does not explicitly name alternatives (e.g., search_users when the exact username is unknown) or state when NOT to use it, so it falls short of a full 5.
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.