cachly-mcp-server

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 explains that the tool 'classifies and stores lessons automatically' and returns 'a summary of what was auto-stored,' which covers basic functionality. However, it lacks details on permissions, rate limits, error handling, or what 'auto-stored' entails (e.g., storage location or format). The description adds some value but misses key behavioral traits 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 front-loaded with the core purpose in the first sentence, followed by usage guidance and return value. It consists of three concise sentences with zero waste, each earning its place by clarifying functionality, timing, and output. The structure is efficient and well-organized.

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 complexity (a mutation tool with no annotations and no output schema), the description is somewhat complete but has gaps. It explains the purpose, usage, and return summary, but lacks details on behavioral aspects like side effects, error conditions, or what the 'summary' contains. For a tool that modifies data, more context on safety and results would improve completeness.

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 100%, so the schema already documents both parameters ('instance_id' and 'observations') and their nested properties. The description mentions 'Pass what happened (commands run, errors seen, solutions found)' which loosely relates to the 'observations' parameter but doesn't add specific syntax or format details beyond what the schema provides. With high schema coverage, the baseline score of 3 is appropriate as the description offers minimal additional parameter insight.

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: 'Auto-learn from a list of session observations WITHOUT explicit learn_from_attempts calls.' It specifies the verb ('auto-learn'), resource ('session observations'), and distinguishes it from the sibling tool 'learn_from_attempts' by emphasizing the automatic classification and storage of lessons. The description is specific and differentiates from 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 provides explicit guidance on when to use this tool: 'Use at session_end to capture everything you did, even if you forgot to call learn_from_attempts.' It contrasts with the sibling tool 'learn_from_attempts' by highlighting the automatic nature and session-end timing, offering clear alternatives and context for usage.

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