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Glama

polaris_events

Poll and acknowledge delivery events from a transactional outbox by consumer, using cursors to resume and prevent redelivery.

Instructions

Consume delivery events published through the transactional outbox.

Actions and required parameters:

  • poll: consumer_id (stable identity, 1-100 chars) — returns events newer than cursor (optional limit). Persist the returned nextCursor between polls; without a cursor you start from the oldest event. After successfully processing events, acknowledge them.

  • acknowledge: consumer_id + event_ids (1-500 ids) — acknowledged events are never redelivered to that consumer; acknowledgement is idempotent per (consumer, event) pair.

Event JSON: {id, type (e.g. EvaluationRecorded, FitnessFunctionVersionActivated), version, aggregateType, aggregateId, occurredAt, actor, correlationId, payload}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
actionYes
cursorNo
all_pagesNo
event_idsNo
consumer_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose key delivery semantics: acknowledged events are never redelivered, acknowledgement is idempotent per (consumer, event) pair, and cursor-less polls begin from the oldest event. It omits rate limits, auth requirements, and concurrency/multi-consumer behavior.

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?

Purpose is front-loaded, actions are bulleted, and the event JSON shape is presented compactly; no sentence is redundant. It is slightly dense but every element (action bullets, event schema) earns its place.

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?

For a 6-param, annotation-less tool with no output schema, it helpfully documents the returned event shape and cursor behavior. The main shortfall is the undocumented all_pages flag and the unstated limit default, so it is nearly but not fully complete.

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?

At 0% schema coverage the description must document all 6 parameters, but it only explains consumer_id (stable identity, 1-100 chars), event_ids (1-500 ids), cursor, and limit (merely 'optional'). The all_pages parameter is never mentioned and limit's default/range is unspecified, leaving real gaps.

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 names a specific verb+resource ('consume delivery events published through the transactional outbox') and enumerates the two concrete actions (poll, acknowledge). No sibling in the list is an event-consumption tool, so the purpose is unambiguous and clearly separable from the polaris_* management/query tools.

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?

It gives explicit workflow guidance: poll returns events newer than cursor, persist nextCursor between polls, start from oldest without a cursor, and acknowledge after successful processing. It never states when not to use the tool or names an alternative action, but the operational sequence is clearly laid out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.