mcp_stats

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

With no annotations, the description carries the full behavioral disclosure burden. It explicitly describes the return dict structure, notes that data is also persisted to a stats JSON file for cross-process visibility, and frames the operation as a snapshot, implying read-only inspection. This is strong context, though it does not discuss any failures or reset behavior.

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 compact: a front-loaded purpose line, a terse return-shape summary, and one sentence about persistence. Every sentence carries useful information with no filler.

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 zero-parameter observability tool with an output schema, the description is complete enough. It explains what the tool does, what it returns, and the cross-process persistence behavior, leaving no critical gap for an agent deciding whether to invoke it.

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 tool takes zero parameters, so the description has no parameter-level semantics to add. The baseline of 4 applies because no input semantics are needed.

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 opens with 'observability — Snapshot of in-memory retry counter per tool,' which names a specific verb, a precise resource, and the tool's scope. This clearly distinguishes it from the unrelated sibling tools such as file_convert, telegram_poll, and trade_signal.

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 'observability' prefix and 'Snapshot of in-memory retry counter' imply this tool is for inspecting retry/event status, but the description does not explicitly state when to prefer it over alternatives or mention sibling tools. Usage context is present but left for the agent to infer.

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