Add rich embedded skills with full test coverage#199
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bussyjd merged 10 commits intooisin/skillsfrom Feb 20, 2026
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Remove hardcoded provider map (anthropic/openai) and instead query the running llmspy pod's providers.json for env var names and available providers. This means any provider llmspy supports (zai, deepseek, google, mistral, etc.) works with `obol model setup` without code changes.
Extract pure functions (parseProviderEnvKey, parseAvailableProviders, buildProviderStatus, patchLLMsJSON) from kubectl-calling wrappers so they can be tested without a running cluster. 23 test cases covering parsing, status cross-referencing, JSON patching, and edge cases.
Adds TestIntegration_ZaiInference that exercises a provider NOT in the old hardcoded map, proving zero-code-change provider support. Uses glm-4-flash via llmspy routing with ZHIPU_API_KEY from .env.
Replace the minimal ethereum skill with three production-ready skills: - obol-blockchain: Ethereum JSON-RPC via eRPC with rpc.py helper, ERC-20 reference, contract addresses, ENS, gas estimation - obol-k8s: Kubernetes cluster diagnostics via ServiceAccount API with kube.py helper for pod/service/event introspection - obol-dvt: Obol DVT cluster monitoring with API examples for validator effectiveness, operator auditing, and exit coordination Keeps the hello skill as-is for smoke testing. Test coverage spans every layer of the skills pipeline: - Unit: embed discovery, copy, skip-existing, volume path, staging, injection, no-op without skills - Integration: staging on sync, pod visibility via kubectl exec, skills sync --from, idempotent re-sync, skill-through-inference (agent references loaded skills), Python smoke tests piped into pod
13 tasks
Replace stale ethereum skill references with the four embedded skills (hello, obol-blockchain, obol-k8s, obol-dvt). Add standalone Skills section to README, update CLAUDE.md delivery flow and source file listings, and expand obol-stack-dev skill with skills system coverage.
…nto feat/rich-skills
…tests - Use glm-5 instead of glm-4-flash (not in providers.json) - Pass explicit instance ID to skills sync when multiple instances exist
Change the name on skills and test
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Summary
Builds on top of #197's host-path PVC injection architecture to add production-ready embedded skills.
ethereumskill withobol-blockchain— 194-line SKILL.md +rpc.pyhelper + ERC-20/contract references + network discoveryobol-k8s— Kubernetes diagnostics via ServiceAccount API withkube.pyhelper (pods, logs, events, deployments, troubleshooting)obol-dvt— Obol DVT cluster monitoring with API examples (validator effectiveness, operator audit, exit coordination)helloas-is for smoke testingZero changes to infrastructure code (
embed.go,openclaw.go,resolve.go, CLI commands).Test coverage
Every layer of the skills pipeline is tested:
TestGetEmbeddedSkillNames,TestCopySkills,TestCopySkillsSkipsExistingTestSkillsVolumePath,TestStageDefaultSkills,TestInjectSkillsToVolume+ edge casesTestIntegration_SkillsStagedOnSync— verifies skills + scripts + references in deployment dir and PVC volumeTestIntegration_SkillsVisibleInPod—lsandheadinside running podTestIntegration_SkillsSync— custom skill viaobol openclaw skills sync --fromTestIntegration_SkillsIdempotentSync— re-sync preserves user customizationsTestIntegration_SkillInference— agent references loaded skills during chat completionTestIntegration_SkillsSmokeTest— 23-assertion Python smoke test piped into pod (rpc.py against eRPC, kube.py against K8s API, DVT API health)Supersedes
Closes #196 — the rich skills content from that PR is integrated here on top of the CTO's host-path injection architecture from #197.