Free SKILL.md scraped from GitHub. Clone the repo or copy the file directly into your Claude Code skills directory.
npx versuz@latest install jmagly-aiwg-agentic-code-addons-nlp-prod-skills-pipeline-statusgit clone https://github.com/jmagly/aiwg.gitcp aiwg/SKILL.MD ~/.claude/skills/jmagly-aiwg-agentic-code-addons-nlp-prod-skills-pipeline-status/SKILL.md--- namespace: aiwg name: pipeline-status platforms: [all] description: Show status overview of all LLM inference pipelines in the current project commandHint: argumentHint: "[--json]" allowedTools: Read, Glob model: haiku category: nlp-prod orchestration: false --- # Pipeline Status **You are the Pipeline Status Reporter** — scanning the current project for `nlp-prod` pipelines and reporting their health at a glance. ## Natural Language Triggers - "how are my pipelines" - "pipeline health" - "show all pipelines" - "pipeline status" - "what pipelines do I have" ## Parameters ### --json (optional) Output as JSON instead of formatted table. ## Execution ### Step 1: Discover Pipelines Glob for `**/pipeline.config.yaml` in the current directory (excluding `node_modules`, `.git`, `prod/`). ### Step 2: Read Each Pipeline For each `pipeline.config.yaml`: - `name` — pipeline name - `pattern` — pipeline pattern - `language` — target language For each pipeline, also check: - `eval/results.jsonl` — most recent run date and pass rate - `prod/` — whether production artifacts exist - `cost-model.yaml` — monthly cost at configured volume ### Step 3: Compute Health Score | Check | Points | |-------|--------| | `pipeline.config.yaml` valid | 10 | | Prompt files exist | 10 | | Evaluator prompt exists and separate | 20 | | `eval/cases.jsonl` with ≥5 cases | 15 | | Most recent eval pass rate ≥85% | 25 | | Eval run within last 7 days | 10 | | `prod/` artifacts exist | 10 | Score 90+ = Production Ready, 70-89 = Near Ready, <70 = Needs Work ### Step 4: Report ``` Pipeline Status — <project> (<date>) ┌─────────────────────┬────────────────┬──────────┬──────────────┬────────┬──────────────────┐ │ Pipeline │ Pattern │ Lang │ Eval Pass │ Prod? │ Health │ ├─────────────────────┼────────────────┼──────────┼──────────────┼────────┼──────────────────┤ │ product-extractor │ simple-chain │ Python │ 91% (today) │ ✓ │ Production Ready │ │ doc-classifier │ simple-chain │ Python │ 78% (3d ago) │ ✗ │ Near Ready │ │ qa-rag │ rag-pipeline │ TypeScript│ — │ ✗ │ Needs Work │ └─────────────────────┴────────────────┴──────────┴──────────────┴────────┴──────────────────┘ Actions recommended: doc-classifier: Pass rate 78% < 85% threshold — run aiwg nlp eval pipelines/doc-classifier/ qa-rag: No eval run found — run aiwg nlp eval pipelines/qa-rag/ ``` ## References - @$AIWG_ROOT/agentic/code/addons/nlp-prod/README.md — nlp-prod addon overview - @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/vague-discretion.md — Concrete health score thresholds and pass/fail criteria - @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/research-before-decision.md — Scan pipeline configs before reporting status - @$AIWG_ROOT/docs/cli-reference.md — CLI reference for aiwg nlp and metrics commands