aiwg
Version:
Deployment tool and support utility for AI context. Copies agents, skills, commands, rules, and behaviors into the paths each AI platform reads (Claude Code, Codex, Copilot, Cursor, Warp, OpenClaw, and 6 more) so one source of truth works across 10 platfo
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Markdown
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