Official Provider SkillView repo
Guide maintainers and contributors through branching, versioning, changelog updates, and publishing agentops-accelerator. Trigger when users ask about branching strategy, creating a release, version tagging, publishing to PyPI, updating the changelog, cutting a release, opening a PR, or syncing a fork. Common phrases include "cut a release", "how do I publish", "create release branch", "tag a version", "update changelog", "release process", "bump version", "what branch should I use", "feature br
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Skill details
Versionv1.0.0
AuthorAzure
Categorydevops
Skill IDAzure/agentops/.github/skills/release-management
Related skills
Agentops AgentAgentOps Doctor - surface release-readiness findings, regressions, latency spikes, error rates, and safety hits across AgentOps eval history, Azure Monitor traces, and Foundry control plane.Agentops AgentAgentOps Doctor - surface release-readiness findings, regressions, latency spikes, error rates, and safety hits across AgentOps eval history, Azure Monitor traces, and Foundry control plane.Agentops ConfigGenerate or update agentops.yaml (flat 1.0 schema) for AgentOps release-readiness gates. Trigger on "configure agentops", "agentops.yaml", "set up evaluation", "what should I evaluate". Infer the agent target and dataset from the codebase; ask only when nothing can be found.Agentops ConfigGenerate or update agentops.yaml (flat 1.0 schema) for AgentOps release-readiness gates. Trigger on "configure agentops", "agentops.yaml", "set up evaluation", "what should I evaluate". Infer the agent target and dataset from the codebase; ask only when nothing can be found.Agentops DatasetCreate or extend a small JSONL dataset for AgentOps release-readiness gates. Trigger on "create dataset", "generate test data", "JSONL", "more eval rows". Infer the agent's domain from the codebase and produce realistic rows; never fabricate data when the domain is unclear.Agentops DatasetCreate or extend a small JSONL dataset for AgentOps release-readiness gates. Trigger on "create dataset", "generate test data", "JSONL", "more eval rows". Infer the agent's domain from the codebase and produce realistic rows; never fabricate data when the domain is unclear.