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codyde
by codyde

list_project_issues

Retrieve and monitor issues from a Sentry project to track status, severity, frequency, and timing for error analysis and debugging.

Instructions

List issues from a Sentry project. Monitor issue status, severity, frequency, and timing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
organization_slugYesThe slug of the organization the project belongs to
project_slugYesThe slug of the project to list issues from
viewNoView type (default: detailed)detailed
formatNoOutput format (default: markdown)markdown
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions monitoring capabilities but doesn't disclose critical behavioral traits such as pagination, rate limits, authentication requirements, or whether it's a read-only operation. For a list tool with zero annotation coverage, this is a significant gap.

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

Conciseness4/5

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

The description is a single, efficient sentence that front-loads the core purpose. It could be slightly more structured by separating monitoring details, but there's no wasted text.

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?

Given 4 parameters with full schema coverage but no annotations and no output schema, the description is minimally adequate. It covers the basic purpose but lacks behavioral context and output details, leaving gaps for an AI agent to infer usage.

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 already documents all parameters. The description doesn't add any meaning beyond what the schema provides, such as explaining the impact of 'view' or 'format' choices. Baseline 3 is appropriate when schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the verb ('List') and resource ('issues from a Sentry project'), and mentions what can be monitored (status, severity, frequency, timing). It distinguishes from siblings like 'list_error_events_in_project' by focusing on issues rather than events, but doesn't explicitly differentiate from 'get_sentry_issue' which retrieves a single issue.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like 'get_sentry_issue' (for single issues) or 'list_error_events_in_project' (for events). The description mentions monitoring aspects but doesn't specify use cases or prerequisites.

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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