Agent Skills: ralph-session-ops-reference
Ralph-v2 session operations reference for schema validation, timeout recovery, and timestamp commands. Use when validating Ralph session artifacts, reconstructing malformed state, enforcing retry timing, or generating Ralph session timestamps.
ID: arisng/github-copilot-fc/ralph-session-ops-reference
Install this agent skill to your local
Skill Files
The files that make up ralph-session-ops-reference.
More agent skills
- diataxisCreate and evaluate documentation using the Diátaxis framework. Use when writing, organizing, or auditing documentation to ensure it serves distinct user needs through four systematic categories (Tutorials, How-to Guides, Reference, Explanation). Ideal for diagnosing documentation problems, separating mixed content, and ensuring each piece serves a single, clear purpose.
- evaluating-sdk-internal-updatesEvaluates a bitwarden/clients "Update sdk-internal to" PR against the sdk-internal commit range for compile-time and runtime breaking changes, maps affected symbols to TypeScript call sites, and applies clear in-scope fixes. Use when reviewing an SDK bump PR, an @bitwarden/sdk-internal version change in package.json, or triaging sdk-internal breaking changes. Requires a sibling `bitwarden/sdk-internal` clone.
- ai-analyzerAI驱动的综合健康分析系统,整合多维度健康数据、识别异常模式、预测健康风险、提供个性化建议。支持智能问答和AI健康报告生成。
- pr-snapshot-releaseGuide a Mastra maintainer through publishing an npm snapshot from a pull request or a specified repository branch. Use when asked to release, publish, or create a PR snapshot, branch snapshot, canary package build, or branch-specific npm tag. Performs source and branch preflight checks, requires confirmation before the irreversible publish, dispatches the existing Publish to npm workflow, monitors it, and reports installable package tags.
- apollo-incident-runbook'Apollo.io incident response procedures.
- ci-metricsQuery PyTorch CI, GitHub Actions, HUD, Grafana, and infrastructure metrics. Use when users ask about CI duration, job failures, queue times, workflow trends, runner health, dashboard data, or PyTorch infrastructure metrics.