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lukleh
by lukleh

search_sonar_issues_in_projects

Search SonarCloud issues across multiple projects, applying severity and pull request filters to reveal defects and code smells.

Instructions

Search issues across one or more projects with optional PR, severity, and pagination controls.

Returns a list of issues matching the filters, with key details like rule, severity, component, and status. Use this to find code quality issues, bugs, vulnerabilities, or code smells in your projects.

Example: search_sonar_issues_in_projects(projects=["my-project"], severities="HIGH,BLOCKER", pullRequestId="123")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pNoPage number (1-indexed)
psNoPage size (max 500)
projectsNoList of project keys to search in (e.g., ['my-project', 'another-project']). Can be omitted to search across all projects in organization
severitiesNoComma-separated impact severity levels. Valid values: 'INFO', 'LOW', 'MEDIUM', 'HIGH', 'BLOCKER'. Example: 'HIGH,BLOCKER'
pullRequestIdNoFilter issues by pull request ID (e.g., '123')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYes
issuesYes
pagingYes
Behavior3/5

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

No annotations are provided, so the description carries the burden. It explains the return format and pagination controls, but it says 'across one or more projects' while the schema allows omitting projects to search all, which is a minor inconsistency. It also doesn't mention edge cases or any side effects, but for a search tool, it covers the basics.

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 concise, front-loaded with the core purpose, and includes a helpful example. Each sentence earns its place, with no redundant fluff.

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

Completeness3/5

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

The tool has an output schema and all parameters are documented, reducing the need for return-format explanations. However, the description's 'one or more projects' phrase contradicts the schema's allowance of omitting projects, creating a completeness gap. The example helps but does not fully compensate for this inconsistency.

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 description coverage is 100%, so the schema fully documents all five parameters. The description adds minimal value beyond the schema, only referencing 'optional PR, severity, and pagination controls' and giving an example. This aligns with the baseline of 3 for high schema coverage.

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 starts with 'Search issues across one or more projects', clearly identifying the verb (search), resource (issues), and scope (projects). It explicitly lists what it does and distinguishes it from sibling tools like search_hotspots and search_quality_gates by focusing on issues.

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 states 'Use this to find code quality issues, bugs, vulnerabilities, or code smells in your projects', providing clear usage context. It doesn't explicitly name alternatives or when not to use, but the context and sibling tools imply the distinction well enough.

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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