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list_events

Retrieve bridge events from the event log with optional filtering by type and notability. Supports cursor pagination for incremental reading.

Instructions

Return bridge events whose ts > since, oldest first.

The event log records dispatch starts/ends, schedule ticks, sentinel hits, schedule completions, webhook outcomes, and recovery actions. The buffer is bounded (default 1000 events) and persisted across bridge restarts.

Two read modes:

  • Debug mode (notable_only=False, the default): every event. Good for forensic post-mortem of a workflow.

  • Surfacing mode (notable_only=True): only state transitions worth reporting to a human — terminal dispatch states, schedule completions / cancellations / errors, webhook failures, recovery actions. Skips dispatch_start, schedule_tick, schedule_created, webhook_sent, and bridge_init_subprocess_alive. This is what an orchestrator wants for "what should I tell the user about?".

Cursor pattern: pass since=0 for everything, then on each subsequent call pass the largest ts you saw.

types is an explicit allow-list — composes with notable_only (intersection).

Common types:

  • Dispatch lifecycle: dispatch_start, dispatch_end, dispatch_cancelled, dispatch_abandoned, dispatch_error, dispatch_orphan_finalized.

  • Schedule lifecycle: schedule_created, schedule_tick, schedule_activated, schedule_self_cancelled, schedule_cancelled, schedule_completed, schedule_tick_error.

  • Webhook outcomes: webhook_sent, webhook_failed.

  • Recovery: bridge_init_recovery, bridge_init_subprocess_alive.

Each event has ts (epoch seconds), event (type), plus type-specific fields (job_id, schedule_id, channel, ok, duration_ms, etc.).

Note: events generated before this feature shipped are gone — the in-memory buffer only captures from the current bridge process onward. Anything you persisted before then lives in the optional CLAUDE_BRIDGE_LOG JSONL file (if you enabled it).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNo
limitNo
typesNo
notable_onlyNo
Behavior5/5

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

No annotations were provided, so the description fully carries the burden. It discloses the bounded buffer, persistence, event loss before feature shipped, optional JSONL log, and event structure. This is thorough behavioral context.

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 detailed and well-structured with sections for modes, common types, and notes. It is front-loaded with the main purpose, though slightly long due to necessary detail. Every sentence adds value.

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

Completeness5/5

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

No output schema exists, but the description adequately describes event structure (ts, event, type-specific fields). It covers usage patterns, edge cases (buffer, persistence, limitations), and provides a complete picture for effective tool use.

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

Parameters5/5

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

Schema description coverage is 0%, but the description adds deep meaning to all 4 parameters: 'since' cursor usage, 'limit' default, 'types' as allow-list with common types, and 'notable_only' with detailed mode definitions. It fully compensates for the schema gap.

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 returns bridge events with filtering, using a specific verb and resource. It distinguishes from sibling tools like list_completions or list_schedules by focusing on the generic event log.

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

Usage Guidelines5/5

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

It explicitly describes two read modes (debug vs. surfacing) with guidance on when to use each, explains the cursor pattern, and details how the 'types' parameter composes with 'notable_only'. This provides clear when-to-use and when-not-to-use advice.

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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