Get full details of a session including message events, tool calls, and metrics. No LLM cost.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | Yes | The agent ID or name | |
| session_id | Yes | The session ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already declares a safe read operation. The description adds the 'No LLM cost' trait, which is useful for cost-aware tool selection, and lists the expected contents (message events, tool calls, metrics). No contradictions with annotations.
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 efficient sentence that front-loads the purpose and includes relevant details without any fluff. 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?
With no output schema, the description clarifies the return contents (message events, tool calls, metrics) and notes the no-cost aspect. It is missing minor details like error behavior or authorization prerequisites, but for a simple read-only get tool, it is sufficiently complete.
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 already fully describes both parameters (agent_id and session_id) with 100% coverage. The description does not add parameter-specific meaning beyond what the schema provides, so the baseline of 3 is appropriate.
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 gets full session details including specific content types (message events, tool calls, metrics). This distinguishes it from sibling tools like kopern_list_sessions, which list sessions, and kopern_get_agent, which gets agent details.
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 implies usage: use this tool when you need full details of a specific session rather than a summary or list. It provides clear context but does not explicitly mention alternatives or exclusions, so it falls short of a 5.
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 have clearly distinct purposes (create vs list vs get vs run vs connect). A few potential overlaps exist (deploy_template vs create_agent, import_agent vs create_agent, grade_prompt vs run_grading) but descriptions clarify the differences.
All tools share the 'kopern_' prefix and mostly follow a verb_noun pattern (create_*, get_*, list_*, run_*, connect_*). The exception is 'kopern_compliance_report', which uses a noun phrase without a verb, breaking the otherwise consistent naming.
With 31 tools, this exceeds the 25-tool threshold for well-scoped servers. While the domain is broad (agent lifecycle, grading, pipelines, teams, connectors), the sheer number of tools feels heavy and could be consolidated (e.g., a single 'manage_memory' tool already bundles multiple actions).
Core agent management (create, read, update, delete, list) is solid, and grading has suite creation, execution, and results. However, pipelines and teams lack get/update/delete operations, connectors only support connect (no disconnect), and there's no way to manage grading suites beyond creation and running. This leaves notable gaps for secondary resources.
