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 describes what the tool returns ('shows author, recency, and severity for each lesson') and the operational context ('shared team brain'), but doesn't cover important behavioral aspects like pagination, error conditions, authentication requirements, rate limits, or whether it's a read-only operation (though 'recall' implies reading).

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 perfectly concise with three sentences that each earn their place: first states the core function, second specifies operational constraints, third provides usage scenarios. No wasted words, well-structured and front-loaded.

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 4-parameter tool with no annotations and no output schema, the description provides good purpose and usage context but lacks details about return format, error handling, and behavioral constraints. It's adequate for basic understanding but incomplete for robust agent operation without additional context about what 'lessons' look like in the response.

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 all 4 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema descriptions, but it does provide overall context about filtering by topic and the team brain concept, which helps understand parameter usage.

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 specific action ('recall lessons'), resource ('shared team brain'), and scope ('showing who learned what'). It distinguishes this tool from sibling tools like 'global_recall' by specifying it works on 'shared team brain' instances for team members, not global recall.

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 clear context for when to use this tool ('to onboard new team members or find who knows about a topic') and specifies it 'works on any shared instance (all team members using the same instance_id)'. However, it doesn't explicitly state when NOT to use it or name specific alternatives among siblings like 'global_recall' or 'smart_recall'.

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