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aiobs_list_sessions

Retrieve AI agent session data from Shepherd to debug runs, compare sessions, track performance, and analyze LLM usage patterns.

Instructions

[AIOBS] List all AI agent sessions from Shepherd. Returns session metadata, labels, and event counts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of sessions to return
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the return content but does not disclose behavioral traits such as pagination, rate limits, authentication needs, or whether it's read-only/destructive. For a list operation with no annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the purpose and output details. Every word earns its place, with no wasted information, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (one optional parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and output but lacks details on usage guidelines and behavioral transparency, which are needed for full completeness in this context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the single parameter 'limit' fully documented in the schema. The description does not add any parameter-specific details beyond what the schema provides, so it meets the baseline of 3 without compensating for gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List all AI agent sessions') and resource ('from Shepherd'), with specific output details ('session metadata, labels, and event counts'). It distinguishes from some siblings like 'aiobs_get_session' (singular) but not explicitly from 'list_sessions' or 'langfuse_list_sessions', which is why it's a 4 rather than a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools (e.g., 'aiobs_search_sessions', 'langfuse_list_sessions', 'search_sessions'), the description lacks any context on use cases, prerequisites, or comparisons, leaving the agent to infer usage.

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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