Create a Grafana annotation with custom text and tags to mark important events or add context for investigating failures, enabling teams to correlate observability data without opening Grafana.
Create a Grafana annotation. This is the write tool for observability.
| Name | Required | Description | Default |
|---|---|---|---|
| tags | No | mcp | |
| text | Yes | ||
| session_name | No | default |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. It states that this is a write tool, which implies mutation, but it does not disclose any requirements around connections, authorization, idempotency, or side effects beyond creating an annotation. The word 'Create' already signals a write, so the description adds little behavioral nuance.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with no redundancy, and the core action is stated first. The second sentence adds useful context by identifying this as the write tool, making every sentence earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple on the surface, but with no annotations and no parameter descriptions, an agent lacks key information needed to call it correctly. It is not told what values are expected for text, tags, or session_name, or whether a prior connection is required. Even for a low-complexity tool, this is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description mentions none of the three parameters (text, tags, session_name). It therefore does nothing to compensate for the schema's lack of explanatory detail. An agent is left to guess what 'text' should contain or what 'session_name' controls.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific action ('Create') and resource ('Grafana annotation'), so an agent knows exactly what operation this performs. The phrase 'write tool for observability' contrasts with read-oriented siblings like obs_query_metrics and obs_get_trace, making its purpose distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies this is the tool to use when writing/creating observability data, and the sibling list makes the alternative read tools obvious. It does not explicitly say 'use this instead of X when you need to annotate,' but the write-vs-read distinction is strong enough for an agent to route correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.