fetch_series

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains that resolution aggregates into UTC-aligned buckets with avg/min/max/count, summary collapses the whole range, top_n filters and sorts buckets, and the result includes total_buckets. This goes well beyond a simple 'fetch' statement, though it does not fully specify the response structure.

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?

The description is efficiently organized: a one-sentence purpose statement followed by compact, scannable sections for each option. Every sentence adds operational value and there is no filler. Parameter names are consistently formatted, aiding quick reference.

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?

For a tool with 11 parameters and no output schema, the description covers the important invocation logic and combination constraints (summary vs resolution, top_n requiring resolution, order/top_by semantics). It even mentions the total_buckets field in the result. The only notable gap is that the exact return format is not described, though the aggregation semantics make it largely inferable.

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%, so the description must compensate. It defines start/end input formats (unix timestamp or rrdtool strings), resolution, summary, top_n, order, and top_by semantics with examples and constraints. However, the identifiers group, host, and plugin are not explicitly explained, leaving some parameters to be inferred from domain knowledge.

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?

Description opens with 'Fetch time series data for a single field,' a specific verb and resource that clearly differentiates it from siblings like list_hosts or get_metadata. The 'single field' qualifier adds precision about what data is returned.

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 gives strong conditional guidance for parameters ('use this for long time ranges to avoid returning hundreds of raw points', 'Cannot be combined with resolution'), but it does not explicitly say when to use fetch_series versus sibling tools such as render_graph or get_metadata. The usage context is mostly implied rather than stated.

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