_mcp_suggest_retraining

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

With no annotations, the description carries full burden for behavioral disclosure. It implies a read-only recommendation via 'recommend' and 'pure', but does not explicitly state side effects, required permissions, or whether the tool modifies state.

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 very concise at 10 words, but the '— pure' adds little value and could be removed. It lacks structure for complex parameters. Still, it is front-loaded with the core purpose.

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 tool has 3 undocumented required parameters and an output schema (not shown). The description fails to map parameters clearly or explain how the recommendation is derived. It is incomplete for effective use without further context.

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 0%, and the description does not elaborate on parameter semantics beyond listing the signal names. There is no explanation of units, ranges, or examples. The description uses slightly different terms ('drift' vs 'drift_magnitude', 'new data volume' vs 'new_data_size', 'staleness' vs 'days_since_last_train'), potentially causing confusion.

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 recommends retraining based on production signals, listing the three signals (drift, new data volume, staleness). It distinguishes from sibling tools like 'trigger_remote_training' which actually executes training. However, the meaning of '— pure' is ambiguous.

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 no guidance on when to use this tool versus alternatives (e.g., 'trigger_remote_training'). It does not mention prerequisites, context, or exclusion criteria.

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