List MQL5 authoring drafts

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

Annotations provide readOnlyHint and openWorldHint, but the description goes further by disclosing that source code, compiler logs, and diagnostics are dropped to avoid >10MB responses, that the cut content is listed in `notes`, and that there is no option to request the unshaped response. This is essential behavioral context beyond the annotations.

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 succinct yet information-dense. It front-loads the core purpose, then use cases, then the critical shaping caveat, all in four sentences. No filler or redundancy; every sentence earns its place.

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?

With an output schema present, the description need not repeat return types, but it adds critical context about dropped fields and size limits that the schema cannot convey. It also covers usage scenarios, ordering, and alternatives, making it complete for an agent to correctly select and invoke this tool.

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?

There are zero parameters, so baseline is 4 per rubric. The description doesn't need to explain parameters, but it effectively communicates the response shape and its implications. Since the schema has no properties to describe, the description adds value by clarifying output details, which is more relevant to contextual completeness.

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 verb (List), the resource (MQL5 drafts), and ownership scope (this API key owns). It also specifies ordering (most recently updated first) and the fields included. It differentiates from siblings by naming get_draft and list_draft_attachments as alternatives for specific needs.

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?

Explicitly tells the agent when to use this tool: to find a draftId, answer 'what am I working on', or identify broken drafts. It also points to sibling tools (get_draft, list_draft_attachments) for source/attachment retrieval, giving clear when-to-use vs. when-not-to-use guidance.

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