get_conceptEach Greenlit book answers one named question (its concept, for example: the green lie). Returns the concept's question, short answer, and full explanation with its book. If the slug is unknown, returns the list of all concept slugs.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The concept slug, e.g. the-green-lie. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavior disclosure. It clearly discloses an unusual behavior: if the slug is unknown, it returns all concept slugs rather than failing. It also clarifies that the returned concept includes its associated book. It does not explicitly state read-only/no-side-effects, but the 'Returns' framing makes that reasonably clear.
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-loads the domain context, then states exactly what is returned and the fallback behavior. Every sentence earns its place with no redundancy or filler.
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?
This is a simple one-parameter read tool with no output schema and no annotations. The description fully covers the return contents, the association with a book, and the unknown-slug fallback. Nothing an agent needs to know to call it correctly is missing.
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 coverage is 100%: the single 'slug' parameter is documented with an example. The description adds context about what happens when the slug is unknown, which is helpful, but it does not add meaning about the parameter itself beyond the schema. Baseline 3 is therefore 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 states a specific verb and resource ('Returns the concept's question, short answer, and full explanation with its book') and clearly defines what a concept is in this domain. The resource is distinct from the sibling tools, so an agent can immediately tell this is for concept lookups by slug.
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 implies when to use the tool: when you have a concept slug and want its question/answer/explanation. It also gives a useful fallback behavior for unknown slugs, but it does not explicitly compare against sibling tools like get_book or search_greenlit_books, nor state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a clearly distinct action: topic discovery, full-text search, book details, concept lookup, free chapter text, and reading paths. The only pair that could overlap—find_books_for_topic and search_greenlit_books—is cleanly separated by curated topic mapping versus ranked full-text search.
Four tools follow the get_* pattern, while the two discovery tools use find_ and search_. This is readable and predictable, with only a minor deviation in verb choice and one name including the server brand.
Six tools is a well-scoped size for a book catalog server. Each tool covers a distinct user need without redundant or bloated surface area.
The surface covers the full reader journey: discover via topic or search, get book details, read the free chapter, understand the concept, and follow a reading path. No obvious dead ends or missing core operations for a catalog-focused server.