list_concepts

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

With no annotations, the description carries full burden. It only states the action but omits behavioral traits such as read-only nature, performance implications, ordering, or whether the output is paginated. 'All' implies a potentially large result, but no caveats are given.

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?

A single, direct sentence is concise and front-loaded. However, it may be too terse, lacking information that could aid an agent without sacrificing brevity.

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?

No output schema or annotations exist. The description does not explain the return format (e.g., list of strings) or any edge cases. For a tool with no parameters and no other documentation, more context would be expected to ensure correct usage.

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 zero parameters and 100% coverage. Per calibration guidelines, 0 parameters earns a baseline of 4. The description adds no parameter semantics, which is acceptable since none exist.

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 uses a specific verb ('list') and resource ('concept names') and implies the scope ('all ... currently stored in memory'). It clearly distinguishes from sibling tools like mcp_engram_list_namespaces that list namespaces, not concepts.

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?

No guidance on when to use this tool versus alternatives (e.g., mcp_engram_read_concept). The description lacks conditions, prerequisites, or exclusions, leaving the agent to infer usage context.

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