mcp_engram_stats

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

With no annotations, the description fully discloses behavior: it calculates and returns a formatted text block with specific metrics. It implies a non-mutating, read-only operation by describing a report generation. It could explicitly state 'no side effects' but the description is otherwise transparent about what happens.

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 structured with clear labels (BEHAVIOR, USAGE, OUTPUT) and only three sentences. Every sentence earns its place, providing key information without redundancy or fluff.

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 no parameters and no output schema, the description fully explains what the tool returns (total memories, pinned count, CRS distributions, active namespace, disk usage) and when to use it. It also connects to the related forget_old tool, making it complete in the given context.

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 tool has zero parameters, so baseline 4 applies. The description adds no parameter details because none exist, but it compensates by describing the output contents in detail, which is more relevant for a no-argument stats tool.

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: 'Calculates and returns a comprehensive health report of the geometric manifold.' It specifies the main outputs (scale, disk usage, active namespace, thermodynamic health) and distinguishes it from other tools by focusing on overall stats rather than specific operations like recall or cleanup.

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 an explicit use case: 'Useful before deciding on explicit bulk cleanup (forget_old).' This gives clear context for when to call the tool. It does not mention exclusions or alternatives, but the specific scenario is sufficient for a stats/reading tool.

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