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recent_events

Read recent workspace activity events from the .nogra events log to inspect public activity recorded through post_event.

Instructions

Read recent workspace activity events.

    Returns recent JSONL event entries from the configured workspace .nogra events log.

    When to use:
    - Inspect recent public workspace activity recorded through post_event.
    - Build caller-driven views over the local event substrate without reading resources directly.

    When NOT to use:
    - Do not use this for run status history; use recent_runs for run updates.
    - Do not use this to append events; use post_event for writes.

    Examples:
    >>> recent_events(limit=20)
    {"workspaceId": "local", "events": [...]}
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of recent workspace events to return.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries full burden for behavioral transparency. It clearly indicates read-only behavior ('Read recent...') and mentions the underlying data source ('.nogra events log'). However, it does not disclose potential limitations such as rate limits or whether events are persisted, but for a simple read tool this is acceptable. Score 4 instead of 5 due to minor omission of side effects.

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 concise and well-structured with sections for purpose, usage guidelines, and an example. Every section is informative and no unnecessary text is present.

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?

Given the tool has only one optional parameter, an output schema (mentioned in context), and clear usage guidelines, the description fully covers what an AI agent needs to use the tool correctly. No gaps remain.

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?

The schema has 100% coverage (limit parameter with description). The description adds an example but no additional semantic meaning beyond what the schema provides. Baseline of 3 is appropriate.

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 it reads recent workspace activity events, using a specific verb ('Read') and resource ('recent workspace activity events'). It distinguishes itself from sibling tools like recent_runs and post_event, making the tool's purpose unambiguous.

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?

The description explicitly states when to use (inspect recent activity, build caller-driven views) and when NOT to use (for run status history or appending events), providing direct alternatives (recent_runs, post_event). This is excellent guidance for AI agent selection.

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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