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post_event

Record a visible workspace activity event with event type and message, optionally linked to a brief or run id, for pinboard or workflow notes.

Instructions

Append a workspace activity event.

    Writes one JSONL event into the configured workspace .nogra events log with schema, id, timestamp,
    workspace id, event type, message, and optional brief/run links, then returns the event id and events
    resource URI.

    When to use:
    - Record a visible workspace activity note for pinboard or workflow surfaces.
    - Attach a lightweight event to a brief id, run id, or both.

    When NOT to use:
    - Do not use this for run status history; use update_run for run updates.
    - Do not use this to store large reports or artifacts; it appends a compact event message.

    Examples:
    >>> post_event("dispatch", "Queued analytics audit", brief_id="brief-123", run_id="run-456")
    {"status": "ok", "eventId": "event-...", "resourceUri": "nogra://workspace/local/pinboard/events"}
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
run_idNoOptional run id to associate with the event; sanitized before storage.
messageYesHuman-readable event message to append to the workspace event log.
brief_idNoOptional brief id to associate with the event; sanitized before storage.
event_typeYesShort event category. Blank input is stored as note.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description discloses the writing behavior, return fields, and lightweight nature. Could be more explicit about side effects or idempotency, but overall adequate.

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?

Well-structured with sections and examples, but slightly verbose. Front-loaded with the core purpose. Good readability.

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?

Covers purpose, usage, parameters, return values (via example), and exclusions. Lacks error handling or rate limits, but given the presence of an output schema and completeness of other aspects, it is sufficient.

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 3. The description adds context about sanitization of IDs, relationship to event structure, and example usage, adding value beyond the schema.

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 appends a workspace activity event and lists the fields. It distinguishes from siblings like update_run and large reports via explicit 'When NOT to use' sections.

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?

Explicit 'When to use' and 'When NOT to use' sections with clear conditions and alternatives (e.g., update_run for run status). Examples further illustrate appropriate 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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