Triage a dotnet/runtime GitHub issue with duplicate search, label check, reproduction, and ecosystem research, then recommend KEEP/CLOSE/NEEDS INFO. Use when asked to triage, evaluate, assess, or check a specific GitHub issue. Also use when asked "is this a duplicate", "should we close this", "check this issue", "what do you think about this issue", or when given a dotnet/runtime issue URL or number and asked for an opinion. Handles bug reports, API proposals, enhancements, performance regressions, and questions.
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Low
Low-risk findings worth noting
Low
Low-risk findings.
2 low severity findings. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
The required workflow explicitly fetches a specified GitHub issue’s body and all comments authored by others (outsider content) and injects that free text into the agent’s LLM context for triage/safety scanning (Step 0 “Fetch the issue first, then scan the fetched content”).
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
The skill includes an explicit runtime command that clones and runs code from https://github.com/dotnet/performance.git (see "git clone https://github.com/dotnet/performance.git" followed by running a Python script), which fetches and executes remote code as part of the performance-triage workflow.
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