MidOS Research Protocol MCP

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

With no annotations provided, the description carries the full burden. It discloses the vector similarity mechanism but fails to state whether the operation is read-only, what similarity threshold is used, or performance characteristics like latency for large memory stores.

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 appropriately concise with a clear single-sentence purpose followed by an Args section. The structure is efficient, though the docstring-style 'Args:' formatting is slightly informal for an MCP description field.

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 simple 2-parameter schema and the presence of an output schema (excusing return value documentation), the description is complete. It covers the tool's purpose, mechanism, and parameter semantics adequately for the complexity level.

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%, requiring the description to compensate. The Args section successfully documents both parameters: 'query' is described as describing the experience/task, and 'limit' includes the default value of 5. This fully compensates for the bare schema.

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 verb (Search), resource (episodic memory), and mechanism (vector similarity). It distinguishes from siblings like 'semantic_search' and 'episodic_store' by specifying 'episodic memory' and 'past experiences', though it lacks explicit contrast with those alternatives.

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 states what the tool does but provides no guidance on when to use it versus similar search tools like 'semantic_search' or 'search_knowledge', nor does it mention prerequisites or exclusions for its use.

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