mcp-memento

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: the tool is for increasing confidence (implying mutation), specifies boost mechanics (e.g., base boost amounts, caps, maximum confidence), and outlines usage contexts. However, it lacks details on permissions, error conditions, or response format, which are minor gaps for a mutation tool.

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 sections ('Use for:', 'Usage patterns:', 'Boost mechanics:'), making it easy to scan. It is appropriately sized for the tool's complexity, with each sentence adding value (e.g., explaining boost amounts and usage scenarios). However, some redundancy exists (e.g., similar points in 'Use for' and 'Usage patterns'), slightly reducing efficiency.

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 tool's moderate complexity (mutation with 4 parameters), no annotations, and no output schema, the description provides good contextual completeness. It covers purpose, usage guidelines, and behavioral mechanics, but lacks details on output (e.g., what is returned after boosting) and error handling, which are minor omissions for an agent's understanding.

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 input schema has 100% description coverage, so the schema already documents all parameters thoroughly (e.g., memory_id, relationship_id, boost_amount, reason). The description adds minimal value beyond this, as it does not explain parameter interactions or provide additional context not in the schema. The baseline score of 3 is appropriate since the schema handles most of the parameter documentation.

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 explicitly states the tool's purpose as 'Boost confidence when a memory is successfully used,' which is a specific verb ('boost') applied to a resource ('confidence' of a memory). It clearly distinguishes this from sibling tools like 'adjust_memento_confidence' (which implies broader adjustments) and 'apply_memento_confidence_decay' (which implies reduction), by focusing on reinforcement after successful use.

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 explicit guidance on when to use this tool through sections like 'Use for:' and 'Usage patterns:', listing specific scenarios such as 'After successfully applying a solution' and 'When verifying old information is still valid.' It also implies when not to use it (e.g., for general confidence adjustments or decay) by contrasting with sibling tool names, though it does not name alternatives directly.

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