Qingflow Canonical Query Plan

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

Annotations (readOnlyHint: true, idempotentHint: true) already declare safety and idempotency. The description adds behavioral context: it normalizes, translates into internal tools, and estimates readiness. This goes beyond annotations by explaining what the tool does to the query, which helps the agent understand the transformation process.

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?

Single sentence, front-loaded with the core action ('Preflight canonical query DSL'), and no redundant words. Every phrase earns its place (normalize, translate, estimate).

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?

Despite having an output schema, the description is insufficient for the tool's complexity. It provides a high-level overview but lacks details on how to structure the query/action objects or interpret results. Parameters are undocumented, and the agent lacks guidance for correct invocation.

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%, so the description must compensate, but it does not. None of the five parameters (kind, query, action, probe, resolve_fields) are explained. The description mentions 'normalize loose inputs' but does not link to any parameter. An agent cannot infer parameter semantics from the description alone.

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's purpose: 'Preflight canonical query DSL, normalize loose inputs, translate into internal tools and estimate whether the query is ready for a final conclusion.' It uses specific verbs and resources (canonical query DSL, internal tools) and distinguishes itself from sibling tools like qf.query.rows or qf.query.aggregate by emphasizing the preflight/normalization role.

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?

No explicit guidance on when to use this tool versus alternatives (e.g., direct querying tools). The description implies it's a preflight step, but does not specify conditions or exclusions. An agent would have to infer usage context without clear direction.

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