Read one MQL5 draft

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

Even though readOnlyHint=true is already annotated, the description adds significant behavioral warnings: the response can be extremely large (up to ~105,000 tokens) because content is returned twice, attachment source code is excluded, and only attachment metadata is included. This gives the agent crucial execution-hazard information 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?

Although it is longer than average, every sentence contributes: what is returned, why to use it, how to reference the parameter, the large-response warning, the attachment behavior, and the cheaper alternative. The most important caveat, response size, is highlighted and placed prominently.

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 read operation with an output schema and readOnlyHint annotations, the description provides all the context an agent needs: return contents, size hazard, attachment source exclusion, and sibling routing. The attachment exclusion is especially important because otherwise an agent would assume the returned source includes attachment code.

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 schema offers 0% description coverage, so the description carries the full burden of explaining the only parameter. It directly defines `draftId` as the `id` field from list_drafts, which is precise, actionable, and sufficient for an agent to invoke the tool correctly.

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 and resource, 'Read one MQL5 draft', and lists exactly what the tool returns: source code, compiler log, diagnostics, and compile-match status. It distinguishes itself from sibling tools by explicitly saying how it differs from list_drafts and list_draft_attachments. This allows an agent to confidently select it for showing code or diagnosing compile failures.

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?

It explicitly tells the agent when to call it: to answer 'why did this fail to compile' or 'show me the code'. It also gives routing alternatives: use list_draft_attachments for attachment source code and list_drafts for a cheap overview. This is strong, actionable usage guidance.

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