list_graphs

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

With no annotations, the description carries the full burden and does well: it discloses that only graphs with at least one triple appear, that empty graphs are indistinguishable from never-created ones on TDB2, and that the default graph is reported separately. It omits auth/rate-limit behavior but covers the subtle semantic quirks a caller needs.

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 core purpose is front-loaded in the first sentence, and the following sentences each add genuine semantic value rather than filler. Slightly verbose, but the length is earned by the non-obvious empty/default graph behavior.

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?

There is no output schema, so the description must convey return content; it does so by stating graphs come with triple counts and that the default graph is reported separately. Complete enough for correct invocation, with only minor gaps around formatting or ordering.

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 coverage is 100% and the single dataset parameter is already documented in the schema. The description adds no parameter details beyond what the schema provides, so the baseline of 3 applies.

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?

States a specific verb and resource ("List the named graphs in a dataset") plus a return detail ("with a triple count for each"). It is clearly distinct from read_graph/drop_graph/write_graph, though it does not explicitly name a sibling to route the agent away from.

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?

Usage is implied through the discussion of empty graphs and default graphs, but there is no explicit when-to-use, when-not-to-use, or alternative tool named. The agent must infer the selection context.

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