save_pipeline

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

Despite no annotations, the description adequately discloses key behaviors: upsert semantics (overwrites if exists), storage scopes (workspace/global/auto), and config format (YAML/JSON). It omits error handling or authentication needs, but covers the most critical aspects.

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 well-structured with a main sentence, a supporting paragraph, an Args list, and a Returns note. Every sentence adds value without redundancy, making it efficient and easy to parse.

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 save tool with 5 parameters (2 required) and no annotations, the description covers purpose, usage, parameter details, and return value. It provides sufficient context for correct invocation, including upsert and scope behavior. No major gaps.

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?

With 0% schema description coverage, the description compensates excellently by detailing each parameter: name constraints (max 64 chars, allowed characters, upsert), config format, tags as comma-separated, description purpose, and scope options with default. This provides full meaning beyond the schema.

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 clearly states the tool saves a pipeline configuration for later reuse, with a specific verb and resource. It distinguishes itself from siblings like load_pipeline and delete_pipeline by emphasizing storage and reuse.

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 explains when to use the tool (to save for later reuse) and gives an example of loading via unified_search. However, it doesn't explicitly exclude alternatives like manage_pipeline or schedule_pipeline for similar tasks, which is a minor gap.

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