List the chapters (table of contents) of a purchased book without downloading the full text. Pass the download_url from the purchase response. Returns each chapter's index, title, and length. Use read_chapter to fetch a single chapter at a time instead of pulling the whole book at once.
| Name | Required | Description | Default |
|---|---|---|---|
| download_url | Yes | The full download URL from the purchase response |
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, the description carries the burden. It discloses the return format ('Returns each chapter's index, title, and length') and the safety of not downloading full text. It doesn't mention permissions, but 'purchased book' implies entitlement, and no contradictions exist.
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, front-loaded with the main action, then parameter, return values, and alternative usage. No filler words, every sentence serves a purpose.
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 single-parameter tool without an output schema, the description covers purpose, parameter source, return shape, and the recommended alternative for fetching chapters. It is fully complete for the tool's complexity.
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 already fully describes download_url as 'The full download URL from the purchase response' (100% coverage). The description essentially repeats this instruction ('Pass the download_url from the purchase response') without adding new semantic detail, so 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 clearly states the tool's verb and resource: 'List the chapters (table of contents) of a purchased book'. It further distinguishes itself by noting 'without downloading the full text' and explicitly contrasts with read_chapter, which fetches a single chapter.
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?
Explicit guidance is provided: 'Use read_chapter to fetch a single chapter at a time instead of pulling the whole book at once.' This names the alternative and the condition for using it, while the primary use case (listing TOC) is implicit and clear.
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.