list_common_errors

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

With no annotations, the description carries full burden. It mentions listing and sorting but does not disclose read-only nature, authorization needs, rate limits, or behavior edge cases (e.g., empty results). Adequate for a simple retrieval tool but limited in transparency.

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 a single concise sentence with an emoji, front-loading the purpose. Every word earns its place with no redundancy.

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?

The description is adequate for a simple tool with one parameter and no output schema, but it lacks details on return structure (fields like error code, message, count). This omission reduces completeness for an agent needing to parse the output.

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% as the only parameter 'limit' is well-described in the schema. The tool description adds no extra meaning to the parameter, so baseline score of 3 applies.

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 lists the most common MQL5 compilation errors sorted by frequency, which is specific and distinguishes it from sibling tools like diagnose_error (for specific errors) and manage_error_db (database management).

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 implies usage for quickly grasping common issues, and the tool name and siblings provide context, but it does not explicitly state when to use this tool over alternatives or define exclusions.

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