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MCP-100

MCP Sentry

by MCP-100

get_sentry_issue

Retrieve and analyze Sentry issues by ID or URL to investigate production errors, access stacktraces, and review error patterns for debugging.

Instructions

Retrieve and analyze a Sentry issue by ID or URL. Use this tool when you need to: - Investigate production errors and crashes - Access detailed stacktraces from Sentry - Analyze error patterns and frequencies - Get information about when issues first/last occurred - Review error counts and status

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issue_id_or_urlYesSentry issue ID or URL to analyze
Behavior3/5

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

No annotations provided, so description carries full burden. Discloses what data is returned (stacktraces, frequencies, first/last occurrence, status) but omits operational concerns: authentication requirements, rate limits, error handling for invalid IDs, or privacy implications of accessing production errors.

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 purpose front-loaded in the first sentence, followed by explicit usage guidelines. Bullet points are specific and non-redundant. Slightly verbose compared to minimalist ideal, but every sentence serves distinct selection or invocation guidance.

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?

For a single-parameter retrieval tool without output schema, description adequately hints at return value structure by listing accessible data types (stacktraces, error patterns, temporal metadata). Missing only operational edge cases; sufficient for agent to understand tool capabilities and expected output richness.

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% (single parameter 'issue_id_or_url' fully documented). Description mentions 'by ID or URL' which aligns with schema but adds no additional semantic value such as format examples, validation rules, or distinction between ID vs URL input behavior. Baseline 3 appropriate for complete 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?

Opens with specific verb+noun combination ('Retrieve and analyze a Sentry issue') and clearly identifies the lookup method ('by ID or URL'). Effectively distinguishes from sibling 'get_list_issues' by emphasizing singular issue retrieval versus listing.

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?

Explicitly prefixes usage scenarios with 'Use this tool when you need to:' followed by five specific bulleted contexts (production errors, stacktraces, error patterns, temporal data, counts/status). Lacks explicit 'when not to use' or named alternative, but sibling tool name provides clear contrast.

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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