get_xgr_docRetrieve canonical Markdown documentation for an XGR/XDaLa topic.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes | Value for the topic parameter. |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | Structured result data returned by the XGR MCP gateway. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false, so the agent knows this is a safe read operation. The description adds minor context ('canonical Markdown documentation') but does not elaborate on error handling or exact behavior beyond what the schema provides.
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 a single sentence (10 words), front-loaded with the verb 'retrieve', and contains no unnecessary information. Every word earns its place.
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 simple parameter (enum), annotations covering safety, and presence of an output schema, the description is mostly complete. It could optionally clarify that the returned documentation corresponds to the specified topic, but the current version is sufficient.
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 description adds meaning beyond the schema: it specifies the output is Markdown documentation and clarifies that the topic is XGR/XDaLa-related. Schema coverage is 100% with an enum, but the schema description for 'topic' is tautological ('Value for the topic parameter'), so the tool description compensates.
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 action ('retrieve') and resource ('canonical Markdown documentation for an XGR/XDaLa topic'). It distinguishes from sibling tools like 'list_xgr_docs' which lists all topics, and other get_ tools that retrieve specific standards or references.
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 no guidance on when to use this tool versus alternatives. No explicit 'when to use' or 'when not to use' is given, and no mention of related sibling tools.
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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There are many overlapping session-listing tools (list_xdala_sessions, get_recent_xdala_sessions, find_latest_xdala_session, list_xdala_session_ids, get_latest_session_payload) and duplicate validation tools (validate_xdala_bundle is an alias for validate_xgr_multibundle). Descriptions help but boundaries are still unclear.
The verb_noun snake_case pattern is consistent across nearly all tools (get_, list_, create_, cancel_, validate_). Minor inconsistencies include the alias validate_xdala_bundle and interchangeable verbs like get_ vs read_ vs resolve_ for similar read operations.
With 95 tools, this is far beyond the 25+ threshold for 'too many'. While the domain is broad, the sheer number makes the tool surface unwieldy and difficult for an agent to navigate.
The tool set covers a wide range of operations: handoffs, session queries, transaction exploration, contract reads, validation, gas requests, and purchases. Minor gaps exist (e.g., no direct workflow editing tools), but overall the surface is remarkably complete.