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Explain quality risk

explain_quality_risk
Read-only

Assess quality risk by analyzing coverage heatmap, execution history, and 30-day trends. Identifies high and medium risk areas to answer whether it is safe to ship or where more tests are needed.

Instructions

Get a quality risk assessment using coverage heatmap, execution history, and 30-day trend data. Identifies high-risk and medium-risk areas. Use to answer questions like 'are we safe to ship?' or 'what areas need more tests?'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
areaNoFocus the risk assessment on categories matching this string.
questionNoSpecific quality question to answer (e.g., 'Is the checkout flow well-tested?').
Behavior4/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the agent knows this is safe. The description adds behavioral context: it uses coverage heatmap, execution history, and 30-day trend data to identify high- and medium-risk areas. This goes beyond annotations, though it does not detail data sources or outputs fully.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the tool's core action and data sources. Every sentence serves a purpose: the first explains what and how, the second gives usage examples. No extraneous words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description partially compensates by stating it identifies high- and medium-risk areas. Parameters are well-documented. However, it does not specify the output format (e.g., a list, scores, or visualization) or how the risk assessment is presented, which could leave the agent uncertain about return structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, with both parameters described sufficiently in the input schema. The description adds example questions but does not elaborate on the 'area' parameter beyond what the schema says. It provides minimal additional semantic value over the schema, so a baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves a quality risk assessment using specific data sources (coverage heatmap, execution history, 30-day trend data) and identifies high/medium risk areas. Example questions like 'are we safe to ship?' further clarify purpose. The name 'explain_quality_risk' matches, and it is distinct from siblings like 'analyze_pr_risk' or 'analyze_release_readiness' which focus on different contexts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance via example questions ('are we safe to ship?', 'what areas need more tests?'), indicating when to use this tool. It does not explicitly state when not to use it or mention alternative tools, but the sibling list implies alternatives exist and the description sets a clear context.

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

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