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agentlens_replay

Replay a past session as a structured, human-readable timeline to review agent decisions, failures, and cost accumulation. Filter by steps or event types for focused post-mortem analysis.

Instructions

Replay a past session as a structured, human-readable timeline.

When to use: To review what happened in a previous session — understand failures, decision patterns, timing, or cost accumulation. Great for debugging or post-mortem analysis.

What it returns: A session header (agent, status, duration, cost, event counts) followed by numbered, timestamped steps with event type icons and context annotations.

Parameters:

  • sessionId (required): The session to replay

  • fromStep/toStep: Replay a specific step range

  • eventTypes: Comma-separated filter (e.g., "llm_call,tool_call")

  • summaryOnly: Set true to get just the summary header (fast for large sessions)

Example: agentlens_replay({ sessionId: "ses_abc123", summaryOnly: true }) → returns session summary without steps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sessionIdYesSession ID to replay
fromStepNoStart step number (0-based)
toStepNoEnd step number (inclusive)
eventTypesNoComma-separated event types to filter (e.g., "llm_call,tool_call")
summaryOnlyNoReturn only the summary header (no steps). Default: false
Behavior4/5

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

No annotations are given, so the description carries the full burden. It discloses the return format (session header with agent, status, duration, cost, event counts, followed by numbered steps) and special behavior like summaryOnly mode for large sessions. This provides sufficient behavioral context beyond the input schema.

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

Conciseness4/5

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

The description is well-structured with clear sections (general purpose, when to use, what it returns, parameters, example). It is informative but not excessively long. The information is front-loaded and each sentence adds value.

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

Completeness4/5

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

Given the tool has 5 parameters with 100% schema coverage and no output schema, the description adequately explains the return values (header plus steps) and parameter nuances. It is complete enough for the tool's complexity, though an explicit note on pagination or step limits would be a minor addition.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds value by explaining the purpose of fromStep/toStep (specific step range), eventTypes (comma-separated filter), and summaryOnly (fast for large sessions). It also provides a concrete example, making parameter usage clearer than the schema alone.

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

Purpose5/5

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

The description clearly states the tool replays a past session as a structured timeline. It uses a specific verb (replay) and resource (session), and the context of debugging or post-mortem analysis distinguishes it from sibling tools like agentlens_sessions or agentlens_analytics.

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

Usage Guidelines4/5

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

The description explicitly provides 'When to use' with concrete scenarios (understand failures, decision patterns, timing, cost accumulation). It lacks explicit 'when not to use' or mention of alternatives, but the provided use cases are clear enough for an AI to decide.

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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