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elad12390

Sentry MCP Server

by elad12390

sentry_pattern_analysis

Identifies and ranks error patterns from Sentry issues by merging near-duplicate titles and grouping by event volume, helping you quickly determine if incident events stem from one dominant problem or many.

Instructions

🧩 Use when the user asks: 'group similar errors', 'what error patterns', 'types of errors', 'categorize errors', 'what's the breakdown', 'do we have one problem or many', or during an incident. Sentry already groups events into issues; this tool ranks those issue groups by event volume and merges near-duplicate issue titles (stripping IDs/UUIDs/numbers) into higher-level patterns. ESSENTIAL for incident triage - instantly see whether you have 1 dominant problem or 50 different ones, and which patterns drive the most events.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax issue groups to scan. Default: 100 (max 100).
queryNoSentry search query to scope the analysis. Default: 'is:unresolved'.
projectNoOptional project slug to scope to one project. Omit for all projects.
reasoningYesExplanation of why you are analyzing patterns.
environmentNoOptional environment filter (e.g. 'production').
time_windowNoHow far back to analyze (statsPeriod). Default: '14d'.
min_occurrencesNoOnly show patterns whose combined event count is at least this. Default: 1.
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses the merging of near-duplicates by stripping IDs, ranking by event volume, and that it's for incident triage. Does not explicitly state side effects, but as a read/analysis tool, it's sufficiently transparent.

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?

Well-structured with use cases front-loaded and explanation following. Slightly verbose but every sentence adds value; could be trimmed slightly.

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 adequately describes the high-level output (patterns and event volumes). For a tool with 7 parameters, it covers the what, why, and how-to-use effectively.

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 covers all 7 parameters with descriptions (100% coverage). The tool description adds no extra semantic value beyond the schema; baseline of 3 applies.

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?

Description clearly states it ranks issue groups by event volume and merges near-duplicates into patterns. It distinguishes from siblings by explicitly carving out use cases for pattern analysis vs. individual issue details or search.

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?

Provides explicit trigger phrases ('group similar errors', etc.) and states it's essential for incident triage. Lacks explicit 'when not to use', but the use cases are well-defined.

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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