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AIops-tools

observability-aiops

create_annotation

Create a Grafana annotation (event marker) to mark significant events on dashboards, with optional tags and dry-run preview.

Instructions

[WRITE][risk=medium] Create a Grafana annotation (an event marker).

Args: text: Annotation text. tags: Optional list of tag strings. dashboard_uid: Optional dashboard UID to attach the annotation to. dry_run: If True, preview without creating. target: Grafana target name from config; omit for the default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
textYes
targetNo
dry_runNo
dashboard_uidNo
Behavior4/5

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

The description includes a '[WRITE][risk=medium]' prefix that explicitly discloses the mutation and risk level, and the 'dry_run' parameter is explained as 'preview without creating.' This adds behavioral context beyond the schema, though it does not mention permissions, rate limits, or side effects after creation.

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 highly concise: a one-line purpose statement followed by a structured list of arguments. No unnecessary words or repetition. The front-loaded purpose makes the tool's intent immediately clear.

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 simple create tool with no output schema, the description covers all parameters and includes the dry-run safety feature. It lacks details like return value or what happens after creation, but these are not essential given the simplicity. The description is substantially complete for an agent to invoke correctly.

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 provides clear explanations for all five parameters: text, tags, dashboard_uid, dry_run, and target. Each has a concise meaning that goes beyond the schema titles, such as 'Optional dashboard UID to attach the annotation to' and 'If True, preview without creating.'

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?

Description clearly states the action: 'Create a Grafana annotation (an event marker).' The verb 'Create' and specific resource 'Grafana annotation' distinguish it from siblings like create_silence or update_dashboard. The parenthetical 'event marker' adds semantic precision.

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

Usage Guidelines2/5

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

No guidance on when to use this tool compared to alternatives. The description only states what it does, without mentioning when to choose it over other creation tools or any prerequisites. It also does not exclude use cases or point to sibling tools.

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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