Build a source-linked briefing for answering a tokenization question: the top passages, entity facts, and source URLs in one prompt-ready block. Use it to ground an answer in verified Stobox knowledge before responding.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| max_chars | No |
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 of behavioral disclosure. It describes what the tool produces (a briefing with passages, facts, URLs) and that it uses 'verified Stobox knowledge,' but it does not reveal whether the operation is read-only, how it handles unknown queries, or any rate limits/error behavior. This is adequate but not rich.
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 core action and output contents, followed by a clear use instruction. Every word earns its place with no fluff 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 simple tool with no output schema, the description covers the main purpose and output content, but it omits parameter semantics (especially max_chars) and any edge-case behavior. It is sufficient for a basic understanding but lacks full completeness for a new 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?
Schema description coverage is 0%, so the description must explain the parameters. It implies 'query' is the tokenization question ('for answering a tokenization question') but never explicitly describes parameters. 'max_chars' is completely undocumented, so the agent has no guidance on how the length limit behaves or why it matters.
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 function with a specific verb and resource: 'Build a source-linked briefing' for answering a tokenization question. It lists concrete output components (top passages, entity facts, source URLs) and positions itself as a prompt-ready aggregation tool, distinguishing it from sibling tools like stobox_knowledge_search or stobox_fact_check.
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 a clear usage context: 'Use it to ground an answer in verified Stobox knowledge before responding.' This tells the agent when to invoke the tool, but it does not explicitly mention alternative tools or situations where it should not be used, so it stops short of a full when/when-not guide.
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.
Each tool has a distinct role: search, lookup, fact-check, related topics, context building, and starting tokenization. The descriptions clearly separate these purposes, so an agent can easily select the right tool without confusion.
All tools share the stobox_ prefix and use snake_case, but the action part mixes verb-first (answer_context, fact_check, start_tokenization) and noun-first (knowledge_search, related_topics, term_lookup) patterns. This inconsistency is minor since the names remain descriptive and readable.
With 6 tools, the server is well-scoped for its purpose: knowledge retrieval and tokenization initiation. Each tool has a clear function and there are no redundant or trivial additions.
The server covers the full knowledge lifecycle: searching, defining terms, exploring relations, verifying facts, building context, and acting on a user's request to start tokenization. No obvious gaps exist for the stated domain.
