Shepherd MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it describes what information is retrieved (trace tree, LLM calls, etc.), it doesn't mention important behavioral aspects like whether this is a read-only operation, what permissions might be required, whether there are rate limits, or what format the response takes. For a tool that retrieves detailed session data with no annotation coverage, this represents significant gaps.

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 extremely concise and front-loaded with all necessary information in a single sentence. It efficiently communicates the tool's purpose and scope without any wasted words. The bracketed system identifier '[AIOBS]' is appropriately placed and doesn't interfere with readability.

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 tool's moderate complexity (retrieving detailed session data), lack of annotations, and absence of an output schema, the description is minimally adequate but has clear gaps. It specifies what information is retrieved but doesn't describe the response format, error conditions, or behavioral constraints. For a tool with no output schema and no annotations, more contextual information would be helpful for an AI agent to use it effectively.

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 input schema has 100% description coverage, with the single parameter 'session_id' clearly documented as 'The UUID of the session to retrieve.' The description doesn't add any additional parameter information beyond what the schema provides, which is appropriate given the high schema coverage. The baseline score of 3 reflects adequate parameter documentation through the schema alone.

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 purpose: 'Get detailed information about a specific AI agent session' with specific components listed (trace tree, LLM calls, function events, evaluations). It distinguishes from siblings like 'aiobs_list_sessions' by focusing on a single session rather than listing multiple. However, it doesn't explicitly differentiate from 'get_session' or 'langfuse_get_session' which appear to be similar tools from different systems.

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. With multiple sibling tools like 'aiobs_list_sessions', 'aiobs_search_sessions', 'get_session', and 'langfuse_get_session', there's no indication of when this specific tool is appropriate versus those other options. The description only states what it does, not when to choose it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.