knowledge_learn_staged

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

No annotations are provided, so the description bears full responsibility. It discloses the staging nature and need for confirmation, but lacks details on side effects, reversibility, or behavior of multiple staging calls. For a write tool, this is insufficient beyond the basic staging concept.

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 consists of two sentences: first states the purpose, second explains the process. No extraneous words; every sentence adds value.

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 simple tool with 2 parameters and no output schema, the description covers the staging workflow and confirmation requirement. It does not mention how to confirm later or integration with sibling tools like knowledge_status, but remains fairly complete.

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 both parameters already described. The description adds context about staging overall but does not enhance parameter-specific meaning beyond the schema. Baseline of 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 explicitly states '暂存待确认知识' (temporarily store knowledge to be confirmed) and '存入 staging 区域' (store in staging area), clearly indicating the tool's purpose of staging knowledge. It distinguishes from sibling tools like knowledge_learn (direct learning) and knowledge_config (configuration) by specifying the staging nature.

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 says '需要确认后才正式入库' (requires confirmation before formal entry), hinting that this tool is for adding knowledge without immediate commitment. It provides clear context but does not explicitly mention when not to use or compare with alternatives like knowledge_learn for direct insertion.

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