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agentic-runtime-debug-loop

Use when debugging a deployed service/profile, investigating CI or Kubernetes runtime failure, explaining deployment drift, or producing a runtime debug session summary

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DolphinAI2026/dolphin-code
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22 de julio de 2026 a las 12:18
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SKILL.md
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name
agentic-runtime-debug-loop
description
Use when debugging a deployed service/profile, investigating CI or Kubernetes runtime failure, explaining deployment drift, or producing a runtime debug session summary
# Agentic Runtime Debug Loop Use this skill when debugging a deployed service/profile and a bounded evidence loop is needed across code, CI/CD, Kubernetes, artifacts, logs, Grafana observability, and Phase 4 runtime resources. ## Phase 6.8A Delegation For product-level diagnostics, construct a `HarnessEvidenceRequest` and use `agentic-harness-evidence-loop` / `agentic-evidence` to collect the local bundle and produce `RepairRoute`. This skill retains service/profile collector knowledge for runtime evidence input, but it is not the product-level evidence loop contract. Do not execute code-changing repair, Git mutation, CI trigger, deploy, rollback, Control Plane writes, or storage upload from this skill. ## Inputs Required: - `service` - `profile` - `plan` If `service`, `profile`, or `plan` is missing, ask for it before starting the session or running remote commands. If a controlled write action may be needed, the plan must contain an `agentic_debug_loop` fenced YAML block. ## Plan Policy Read the implementation plan before remote commands. The policy shape is: ```yaml agentic_debug_loop: max_iterations: 3 success_criteria: - "Kubernetes pods for app-api are ready" - "latest CI pipeline succeeds" allowed_actions: - jenkins.build - gitlab.run_pipeline - kubernetes.rollout_restart allowed_resources: - main-postgres - main-redis ``` No `agentic_debug_loop` block means one read-only iteration. Do not execute write actions without explicit `allowed_actions`. ## Session Commands Start a session: ```bash bin/agentic-runtime --json loop start --service <service> --profile <profile> --plan <plan> ``` Record each material command: ```bash bin/agentic-runtime --json loop record-step --session <session-id> --kind status --status ok --summary "<short summary>" --evidence <path> ``` Finish after writing the runtime summary: ```bash bin/agentic-runtime --json loop finish --session <session-id> --final-status <fixed|likely_fixed|not_fixed|blocked|error> --summary-path <summary-path> ``` Session records are written under `.generated/runtime/debug-sessions/`. ## Workflow 1. Parse the plan policy and start a debug session. 2. Run local-only checks: ```bash bin/agentic-runtime --json status --service <service> --profile <profile> --local-only bin/agentic-runtime --json correlate --service <service> --profile <profile> --local-only ``` 3. Run remote read-only evidence commands: ```bash bin/agentic-runtime --json status --service <service> --profile <profile> bin/agentic-runtime --json correlate --service <service> --profile <profile> bin/agentic-runtime --json observe doctor --service <service> --profile <profile> bin/agentic-runtime --json observe metrics --service <service> --profile <profile> bin/agentic-runtime --json observe logs --service <service> --profile <profile> bin/agentic-runtime --json observe trace --service <service> --profile <profile> --trace-id <trace-id> ``` 4. Inspect evidence in this order: - config/parameter resolution - CI status and logs - artifact existence and digest/tag - deployed Kubernetes image - Kubernetes pod state, events, and logs - Grafana observability metrics, logs, dashboard links, and trace hints - configured debug_loop resource hints 5. If status, logs, or correlate evidence includes a trace id or request id, run trace lookup before Phase 4 resource checks: ```bash bin/agentic-runtime --json observe trace --service <service> --profile <profile> --trace-id <trace-id> ``` Record the result with `--kind observability`. 6. Record observability commands with `--kind observability` and evidence paths under `.generated/runtime/observability/`. 7. When evidence points to a data or middleware issue, run resource doctor before query or inspect: ```bash bin/agentic-runtime --json resource doctor --target <resource-id> ``` 8. Query or inspect only resources allowed by the plan and service/profile config. 9. Search code/config only after evidence points to a likely area. 10. If a controlled action is authorized, run dry-run before confirm: ```bash bin/agentic-runtime --json act --service <service> --profile <profile> --action <action> --plan <plan> --dry-run ``` Inspect the dry-run target, parameters, risk, and confirmation id. Run `--confirm` only when the action is listed in `allowed_actions` and the plan policy unambiguously authorizes automated confirmation for the current loop. If that authorization is absent or ambiguous, stop and ask for a plan update or human direction. ```bash bin/agentic-runtime --json act --service <service> --profile <profile> --action <action> --plan <plan> --confirm <confirmation-id> ``` 11. Re-observe status if iterations remain. 12. Write the runtime summary and finish the session. ## Stop Conditions - Stop when success criteria are met. - Stop when `max_iterations` is exhausted. - Stop when required secrets, kubeconfig, or runtime config are missing. - Stop when Grafana observability is configured but its required secret env vars are missing. - Stop when an unlisted action or resource is needed. - Stop when Phase 4 resource safety blocks the operation. - Stop if evidence is contradictory; summarize the contradiction and ask for human direction.
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