create_topicGenerate a new sourced encyclopedia article from a title (web search + LLM, ~15s). Returns the existing article instead if the topic is already covered. Daily rate limit applies — search first.
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
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 full burden and does well: it discloses that the tool performs web search plus LLM generation, takes about 15 seconds, returns existing content when duplicates exist, and has a daily rate limit. These are material behavioral details beyond the name and schema.
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 with no filler. The core action is front-loaded, and the caveats about duplicates and rate limits are packed efficiently into the second sentence.
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 one-parameter creation tool with an output schema, the description covers the essential operational context: what it does, how long it takes, duplicate behavior, and rate limits. The agent has enough information to invoke it correctly and avoid unnecessary calls.
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?
There is only one parameter, title, and schema description coverage is 0%. The description compensates by explaining that the tool generates the article 'from a title,' clarifying the role of the parameter. It does not specify formatting constraints, but for a single simple string parameter that is a minor gap.
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 and resource: 'Generate a new sourced encyclopedia article from a title.' It clearly distinguishes this creation operation from sibling tools like read_topic and search_topics, and even states the duplicate-handling behavior.
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 usage guidance: search first, and if the topic is already covered, the existing article is returned instead of creating a new one. This tells the agent when to avoid calling the tool and implies the alternative search_topics.
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.
Most tools map cleanly to distinct actions like create, read, edit, and search. The main ambiguity is between search_topics and discover_topics, though the descriptions clarify keyword vs. semantic retrieval.
All tool names follow a consistent lowercase verb-first pattern: create_, discover_, edit_, list_, preview_, read_, search_. This makes the expected action immediately clear and predictable.
Seven tools is well-scoped for an encyclopedia server, covering search, discovery, reading, creating, editing, demand insight, and pre-authoring previews. Each tool serves a distinct step without unnecessary bloat.
The core lifecycle is covered: discover and read topics, create missing ones, edit sections, and preview phrases before committing. Deletion is absent but is reasonably not part of this shared knowledge-base workflow.