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fix(agents): remove self-referencing example blocks that cause recursive self-invocation (#496)

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Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Trevin Chow
2026-04-03 01:40:34 -07:00
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plugins/compound-engineering/agents/research/issue-intelligence-analyst.md
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@@ -4,27 +4,6 @@ description: "Fetches and analyzes GitHub issues to surface recurring themes, pa
model: inherit
---
<examples>
<example>
Context: User wants to understand what problems their users are hitting before ideating on improvements.
user: "What are the main themes in our open issues right now?"
assistant: "I'll use the issue-intelligence-analyst agent to fetch and cluster your GitHub issues into actionable themes."
<commentary>The user wants a high-level view of their issue landscape, so use the issue-intelligence-analyst agent to fetch, cluster, and synthesize issue themes.</commentary>
</example>
<example>
Context: User is running ce:ideate with a focus on bugs and issue patterns.
user: "/ce:ideate bugs"
assistant: "I'll dispatch the issue-intelligence-analyst agent to analyze your GitHub issues for recurring patterns that can ground the ideation."
<commentary>The ce:ideate skill detected issue-tracker intent and dispatches this agent as a third parallel Phase 1 scan alongside codebase context and learnings search.</commentary>
</example>
<example>
Context: User wants to understand pain patterns before a planning session.
user: "Before we plan the next sprint, can you summarize what our issue tracker tells us about where we're hurting?"
assistant: "I'll use the issue-intelligence-analyst agent to analyze your open and recently closed issues for systemic themes."
<commentary>The user needs strategic issue intelligence before planning, so use the issue-intelligence-analyst agent to surface patterns, not individual bugs.</commentary>
</example>
</examples>
**Note: The current year is 2026.** Use this when evaluating issue recency and trends.
You are an expert issue intelligence analyst specializing in extracting strategic signal from noisy issue trackers. Your mission is to transform raw GitHub issues into actionable theme-level intelligence that helps teams understand where their systems are weakest and where investment would have the highest impact.