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Manage GitHub Actions workflows and runs via gh CLI.
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Based on SOC occupation classification
Recursive error-fix loop. Use when a bash command fails with a build/test/typecheck error, when the same class of error appears more than once, or when the harness itself needs a persistent rule so the error does not come back. Detect → root-cause → minimal fix → test → lint/typecheck → persist rule (SKILL.md / AGENTS.md / docs/rules) → audit with evidence. Cross-harness (Claude Code, OpenCode, Codex, Gemini, Agy).
Wraps any external CLI so the AI harness can invoke it without context bloat. Captures --help output, documents every subcommand/flag in a compact digest, saves token metrics (raw vs wrapped), and exposes a standardized interface (invoke, explain, audit). Use before calling an unfamiliar CLI or when the harness needs to interact with a CLI repeatedly.
One-shot setup that configures the CLI wrapper ecosystem across ALL AI harnesses (Claude Code, Gemini, Codex, Agy, OpenCode). Creates symlinks from Claude (single source of truth) to every other CLI, registers wrapper skills/agents in each harness, and injects the "prefer wrapped CLI" policy into each CLI's config file. Run once per machine or after adding a new CLI to the ecosystem.
Cross-harness skill that teaches Claude Code, Codex (OpenAI), and Antigravity (Agy) how to use OpenCode as a subagent. Covers delegation triggers, task formatting, provider routing, result handling, and the complete protocol for efficient subagent orchestration.
Automatically routes tasks to the optimal AI agent, model, or provider based on complexity, cost, and capability. Use when implementing features, fixing bugs, or any multi-step development work. Triggers on "implement", "build", "create", "fix", "add feature", "develop", or when the user asks to do any coding task.
Surface opportunities to deepen a codebase. Finds modules that are shallow (thin pass-throughs, anemic types, missing domain modeling) and proposes how to make them deep (rich domain types, co-located behavior, testable seams). Outputs a visual HTML report and then runs an interactive grilling loop that pressure-tests each opportunity. Use when the codebase feels "flat", domain logic leaks into controllers/UI, types carry no behavior, or AI agents struggle to navigate the module boundaries. Integrates with domain-modeling, codebase-design, and ADR workflows.
| name | gh-workflow |
| description | Manage GitHub Actions workflows and runs via gh CLI. |
List, view, run, and manage GitHub Actions workflows.
gh workflow list --limit <n> --all|--enabled|--disabledgh workflow view <id|name> or gh workflow view <id|name> --yaml (show source YAML)gh workflow run <id|name> --ref <branch> -f <key>=<value>gh run list --limit <n> --workflow <id|name> --branch <branch> --status <status>gh run view <run-id> --log or gh run view --job <job-id> or gh run view --webgh run cancel <run-id>gh run rerun <run-id> --failed (only failed jobs) or gh run rerun <run-id> (all)gh run download <run-id> [--dir <dir>]gh run watch <run-id> (live output)gh workflow listgh run view <run-id> --log-failedgh run download <run-id>Triggered when user says "workflow", "actions", "run workflow", "check CI", "view action run".
Use --json flag with gh run list to get structured data. Use --branch to filter runs.