Borrowing it
Nothing to install: this file belongs to Anbu-00001/Sentinel-AIOps. 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/Anbu-00001/Sentinel-AIOps/main/AGENTS.mdgit clone --depth 1 https://github.com/Anbu-00001/Sentinel-AIOpsWrote 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/instructions/anbu-00001/sentinel-aiops/agents-md)<a href="https://agentmods.dev/instructions/anbu-00001/sentinel-aiops/agents-md"><img src="https://agentmods.dev/badge/instructions/anbu-00001/sentinel-aiops/agents-md/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/instructions/anbu-00001/sentinel-aiops/agents-md"><img src="https://agentmods.dev/badge/instructions/anbu-00001/sentinel-aiops/agents-md.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 | $0.00520 | $0.00520 |
| Opus 5 | $0.00260 | $0.00260 |
| Sonnet 5 | $0.00104 | $0.00104 |
| Haiku 4.5 | $0.00052 | $0.00052 |
Grade A, and why
Sentinel-AIOps AGENTS.md scanned grade A with 0 findings 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 9d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🛡️ Sentinel-AIOps Mission Briefing
🎯 Project Mission
Sentinel-AIOps is an autonomous system designed for CI/CD log anomaly detection and remediation within the Antigravity ecosystem.
🧠 Technical Core
Our intelligence relies on Python-based Machine Learning models:
- LightGBM Multiclass Classifier: Supervised model classifying CI/CD logs into 10 failure categories using numerical telemetry features (CPU usage, build duration, memory consumption, retry count). Macro F1 ≈ 0.89 on a balanced 10-class test set. Ablation-verified: removing TF-IDF features reduces F1 by only 0.004 points, confirming the model learns from operational telemetry — not log text.
- Isolation Forest: Unsupervised anomaly detector for out-of-distribution logs that don't match any known failure pattern, flagging novel infrastructure incidents.
- PSI Drift Monitor: Population Stability Index tracking that compares live inference distributions against the training baseline across all numerical and categorical features. Triggers a retrain recommendation when any feature PSI exceeds 0.20.
🏗️ Infrastructure
The system follows a robust, local-first architecture:
- Inference Engine: Powered by a FastMCP server for low-latency, localized model inference.
- Observability Interface: A FastAPI dashboard providing real-time health badges, PSI drift heatmaps, inference history, and GitHub webhook ingestion.
📜 Workflow Rules
All autonomous agents interacting with this project MUST adhere strictly to the following operational protocols:
- Always log 'Reasoning' before execution: Every action must be preceded by a clear, documented rationale.
- Save all ML metrics as 'Artifacts': Performance metrics (specifically F1-Score and PR AUC) must be rigorously tracked and saved as permanent project artifacts.
📁 Directory Map
The project is structurally divided into the following key domains:
/data: For storing raw logs and processed datasets used in model training and inference./models: For housing the trained weights and configurations of our Isolation Forest and LightGBM models./mcp-server: For containing the FastMCP-based local inference logic and API endpoints./dashboard: For the Next.js frontend code providing the observability and monitoring interface.
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.
- 9d ago First seen · 39 lines · 520 tokens per session scan A efc46a5ded38
Sentinel-AIOps AGENTS.md is an instructions file published in the GitHub repository Anbu-00001/Sentinel-AIOps (2 stars, last pushed 4mo ago), licensed MIT. It adds 520 tokens to every session, about $0.0026 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.