mcp_engram_track_user

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

With no annotations provided, the description fully details the behavior: recording interaction, applying an EMA algorithm, and outputting a confirmation. It could mention side effects (e.g., whether it updates a cumulative model) but the core mechanism is transparent.

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 clear 'BEHAVIOR', 'USAGE', and 'OUTPUT' sections. Every sentence adds essential information without redundancy, making it concise and efficient.

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 tool with one simple parameter and no output schema, the description covers all necessary aspects: what it does, when to use, how it behaves, and what to expect as output. It is complete for the agent to select and use correctly.

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?

The schema defines 'interaction' as 'The interaction text to track', and the description adds semantic context: 'significant preference, intent, or constraint', and 'user interaction'. This enhances understanding beyond the schema alone.

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 action: 'Tracks and records a user interaction' into a specific model. It distinguishes from siblings by emphasizing it targets the 'User Model manifold' and uses '90/10 EMA superposition', which is unique among related tools.

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?

Explicitly states when to call ('whenever the user expresses a significant preference, intent, or constraint'), providing clear context. It does not mention alternatives or when not to use, but the guidance is direct and actionable.

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