add_knowledge

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states this is a write operation ('Write new knowledge'), implying mutation, but doesn't address critical aspects like permissions needed, whether writes are permanent or reversible, rate limits, or what happens on success/failure. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.

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 concise and well-structured in two sentences. The first sentence clearly states the core purpose, and the second provides helpful examples of what can be stored. There's no wasted language, though it could be slightly more front-loaded with critical behavioral information given the lack of annotations.

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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't address what happens after writing (success indicators, error conditions, return values) or important behavioral constraints. While the purpose is clear, the lack of transparency about this write operation's consequences makes it inadequate for safe agent use.

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 description coverage is 100%, so the schema already documents both parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't elaborate on 'content' format or 'topic' auto-detection logic). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

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's purpose: 'Write new knowledge to your base' specifies the action (write) and resource (knowledge base). It distinguishes from siblings like 'query_knowledge' or 'search_knowledge' by focusing on creation rather than retrieval. However, it doesn't explicitly contrast with 'capture_session' or 'recall_memory', leaving some sibling differentiation incomplete.

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 minimal usage guidance. It suggests storing 'facts, decisions, patterns, or any information your AI should remember', which implies context but doesn't specify when to use this tool versus alternatives like 'capture_session' for session-based storage or 'recall_memory' for memory retrieval. No explicit when-not-to-use or prerequisite information is included.

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