save_memory

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

With no annotations provided, the description carries the behavioral disclosure burden. It does reveal that the memory goes to a shared team knowledge base visible to team members and AI agents, which is useful. However, it does not mention side effects like creating a new entry, deduplication, overwrite behavior, permissions, or how failures are surfaced.

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 front-loaded purpose statement followed by a compact Args list. Nearly every line adds value, though the list of examples in the second sentence could have been trimmed without losing much.

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?

The tool has five parameters and no schema-level descriptions, yet the description documents all of them and gives useful examples. An output schema is present, so omitting return-value details is acceptable. The main missing element is explicit routing against sibling tools, but the description is otherwise sufficient for a straightforward write operation.

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 0%, so the description must compensate for parameter meaning. The Args block does this well: it explains content, author, tags with an example, file_path relevance, and memory_type allowed values. This is a meaningful addition over the bare schema property titles and types.

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 opens with a clear verb and object: 'Save a memory to the shared team knowledge base.' It then gives concrete examples of what to store, such as architecture decisions, patterns, bugs, and conventions. It does not explicitly name or contrast siblings like bulk_save_memories or update_memory, so it stops short of full sibling differentiation.

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 gives explicit usage context: 'Use this to store architecture decisions, patterns, bugs, conventions, or any context useful for team members and AI agents.' This tells an agent when the tool is appropriate. It does not describe when-not-to-use or point to exact alternatives like update_memory or bulk_save_memories, so comprehensive routing guidance is missing.

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