memory_export_dataset

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

Annotations provide readOnlyHint=true and no destructive hint. Description adds that it is read-only, quality-filtered by importance/confidence, and emits JSONL without modifying state. This adds value beyond annotations, though could mention pagination or behavior on empty results.

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 sentences with no wasted words. First sentence states core purpose and output shape, second clarifies safety and output file format. Highly concise and front-loaded.

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 read-only export tool with 6 parameters and no output schema, the description covers purpose, filters, output format, and safety. It doesn't detail output field structure or edge cases, but is sufficient 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.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear descriptions. The description reinforces the meaning of min_importance/min_confidence and format, but does not add new information beyond the schema. Baseline 3 is appropriate.

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 states a specific verb ('export'), resource ('high-signal rows...as instruction→output training pairs'), and differentiates from siblings by focusing on training data generation for LoRA/distillation. It clearly identifies the tool's intent.

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 implies when to use (generating training data) and contrasts with the generic 'memory_export' sibling, but lacks explicit when-not-to-use guidance or alternative recommendations. Usage context is clear but not exhaustive.

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