qa_probe_label

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

With no annotations, the description carries the full behavioral burden. It discloses that the label reapplies on future runs and explains verdict groups (suppress vs confirm), but it does not mention permissions, reversibility, or what happens with multiple labels for the same endpoint.

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 two sentences plus a concise example. It is front-loaded with the core purpose and contains no redundant information.

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?

Given the tool has 4 parameters and no output schema, the description covers the main purpose and gives a usage example, but it lacks details on persistence behavior, default signal handling, and prerequisites like needing a prior diagnosis report.

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 coverage is 100%, so the baseline is 3. The description adds value by explaining the verdict groups and providing an example, but it does not elaborate on parameter semantics beyond what the schema already offers.

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 states 'Record feedback on an endpoint diagnosis so qa-probe reapplies it on future runs,' which provides a specific verb and resource. It also distinguishes the tool's purpose from siblings by focusing on labeling/teaching behavior, but it could be more precise about what constitutes a label.

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 when providing feedback on a diagnosis ('mark a result as expected/known or confirm it as a real bug') and gives an example, but it does not explicitly state when not to use this tool or compare it to siblings like qa_probe_explain_failure or qa_probe_run_analysis.

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