Borrowing it
Nothing to install: this file belongs to DuqueOM/ML-MLOps-Portfolio. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/DuqueOM/ML-MLOps-Portfolio/main/.devin/skills/debug-ml-inference/SKILL.mdgit clone --depth 1 https://github.com/DuqueOM/ML-MLOps-PortfolioWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/duqueom/ml-mlops-portfolio/debug-ml-inference)<a href="https://agentmods.dev/skills/duqueom/ml-mlops-portfolio/debug-ml-inference"><img src="https://agentmods.dev/badge/skills/duqueom/ml-mlops-portfolio/debug-ml-inference/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/duqueom/ml-mlops-portfolio/debug-ml-inference"><img src="https://agentmods.dev/badge/skills/duqueom/ml-mlops-portfolio/debug-ml-inference.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00020 | $0.02202 |
| Opus 5.5 | $0.00008 | $0.00881 |
| Sonnet 5.5 | $0.00004 | $0.00440 |
| Haiku 4.5 | $0.00002 | $0.00220 |
Grade A, and why
debug-ml-inference scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Bash(curl:*) How it starts
The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug ML Inference
Systematically diagnose and fix ML inference issues in production FastAPI services.
Inputs
$service-name: Name of the ML service to debug (e.g.,bankchurn)
Goal
Identify the root cause of the inference issue and either fix it or provide a specific remediation plan with commands. Every check must produce evidence (command + output).
Steps
1. Anti-Pattern Checklist (DO THIS FIRST)
Run this diagnostic before deep debugging — most inference issues match one of these patterns:
| # | Check | Command | Pass If |
|---|---|---|---|
| D-01 | Multiple workers | grep -rn "workers" $service-name/Dockerfile $service-name/k8s/ |
--workers absent or exactly 1 |
| D-02 | Memory HPA | grep -n "memory" $service-name/k8s/base/*hpa* |
Empty output |
| D-03 | Sync predict | grep -rn "\.predict|predict_proba" $service-name/app/ |
Direct model calls only inside sync helpers delegated by run_in_executor |
| D-04 | TreeExplainer | grep -rn "TreeExplainer" $service-name/ |
None, or only in try/fallback |
| D-05 | == pinning |
grep "==" $service-name/requirements.txt |
No ML packages with == |
| D-06 | Suspiciously high metric | Check MLflow: primary > 0.99? | Below 0.99 |
| D-07 | SHAP background | Check background has both classes | Both high/low probs |
| D-08 | Uniform PSI bins | grep -n "np.linspace|uniform" $service-name/src/*/monitoring/ |
Uses np.percentile |
| D-09 | Missing heartbeat | grep -n "heartbeat" $service-name/k8s/ monitoring/ |
Alert rule exists |
| D-10 | tfstate in git | git ls-files | grep tfstate |
Empty output |
| D-11 | Model in Docker | grep -n "COPY.*model|ADD.*model" $service-name/Dockerfile |
No matches |
| D-12 | No quality gates | grep -rn "quality_gate|should_promote" $service-name/src/ |
Gate logic exists |
| D-21/D-22 | Blocking prediction logs | grep -rn "log_prediction" $service-name/app/ |
Logging is fire-and-forget and errors are swallowed |
| D-23 | Probe split | grep -rn '"/health"|"/ready"' $service-name/app/ $service-name/k8s/ |
/health is liveness, /ready gates on model + warm-up |
| D-24 | SHAP rebuild per request | grep -rn "KernelExplainer" $service-name/app/ |
Built once during artifact load/warm-up, not inside endpoint |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 203 lines · 20 tokens per session scan A 3db7ac6f9e80
debug-ml-inference is a skill published in the GitHub repository DuqueOM/ML-MLOps-Portfolio (7 stars, last pushed yesterday), licensed MIT. It adds 20 tokens to every session and 2,202 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
debug-ml-inference compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| debug-ml-inferenceDuqueOM/ML-MLOps-Portfolio | Skill | 7 | yesterday | MIT | A | 20 | Claude Code |
| mlopswilliamzujkowski/standards | Skill | 19 | 2mo ago | MIT | A | 45 | Claude Code, Codex |
| setupmlflow/mlflow | Skill | 29k | yesterday | Apache-2.0 | A | 10 | Claude Code |
| rocketride-debugging-pipelinesrocketride-org/rocketride-server | Skill | 20k | yesterday | MIT | A | 67 | Claude Code, Codex |
| trulens-instrumentationtruera/trulens | Skill | 3.6k | yesterday | MIT | A | 25 | Claude Code, Codex |
| logging-patternspiomin/claude-ai-spring-boot | Skill | 1.4k | 7d ago | Apache-2.0 | A | 50 | Claude Code |
| starlark-devkurtosis-tech/kurtosis | Skill | 558 | 4d ago | Apache-2.0 | A | 50 | Claude Code, Codex |