KSJ 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 the tool as a read operation ('Return all Synthesis entries') and specifies the output format and ordering, which is helpful. However, it lacks details on potential limitations like pagination, rate limits, or error conditions, which are important for a tool that might return large datasets.

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 appropriately sized and front-loaded, with the first sentence stating the core functionality clearly. Each subsequent sentence adds meaningful context without redundancy, such as detailing the returned fields and the tool's purpose for tracking thinking evolution. There is no wasted text, making it efficient and well-structured.

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 (0 parameters, no annotations, but with an output schema), the description is mostly complete. It explains what the tool does, the data returned, and its use case. Since an output schema exists, it need not detail return values, but it could benefit from mentioning behavioral aspects like performance or data scope. Overall, it covers the essentials well.

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 0 parameters with 100% coverage, so the schema fully documents the absence of inputs. The description adds value by explaining that no parameters are needed and implicitly clarifies the scope ('all Synthesis entries'), which compensates for the lack of parameters. It does not need to detail parameters, so a baseline of 4 is appropriate.

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 with specific verbs ('Return all Synthesis entries') and resources ('Synthesis entries'), distinguishing it from siblings like 'search_captures' or 'find_connections' by focusing exclusively on SYN entries. It explicitly mentions what data is returned ('breakthrough field, patterns identified, $ insight tags, and topic tags') and the chronological ordering, making the purpose unambiguous.

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 see how your thinking has evolved and which ideas led to the biggest discoveries'), implying it's for retrospective analysis of breakthroughs. However, it does not explicitly state when not to use it or name alternatives among sibling tools, such as 'search_captures' for filtered results, leaving some guidance gaps.

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