import_graph

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

No annotations are provided, so the description carries full burden. It discloses auto-format detection, compatibility, and skip behaviors (duplicates, missing entities). However, it does not mention whether the import is destructive (overwrites), what happens on error, or return value details (output schema exists but not described).

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 very concise, with two short paragraphs. All sentences add value: main purpose first, then compatibility and behaviors. No wasted words.

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?

Given the tool's complexity (import with auto-format detection, skip logic) and the lack of annotations or parameter descriptions, the description covers key behaviors but misses details like expected data structure, success/error handling, and performance implications. Output schema exists, so return value documentation is not required, but more context would be helpful.

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 adds some meaning by stating the data parameter expects JSON or JSONL format. But it does not specify the expected structure (e.g., entities and relations array) or provide examples, leaving ambiguity.

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 it imports knowledge graph data and specifies auto-detection of JSON/JSONL formats. It also mentions compatibility and skip behaviors. However, it does not explicitly differentiate from sibling tools like create_entities, which also creates entities but individually.

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 provides context about compatibility with old server-memory files and mentions skip behaviors, implying usage. But it lacks explicit when-to-use/when-not-to-use guidance and does not name alternatives like create_entities for bulk vs individual imports.

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