Monitoring Observability
yonatangross/orchestkit
Monitoring and observability patterns for Prometheus metrics, Grafana dashboards, Langfuse v4 LLM tracing (astype, scorecurrentspan, shouldexportspan, LangfuseMedia), and drift detection.
Implement comprehensive observability for LLM applications including tracing (Langfuse/Helicone), cost tracking, token optimization, RAG evaluation metrics (RAGAS), hallucination detection, and…
Install AI Observability
$ npx skills add omer-metin/skills-for-antigravity --skill ai-observability -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install omer-metin/skills-for-antigravity ai-observability --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/omer-metin/skills-for-antigravity.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-observability .claude/skills/ai-observability && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "ai-observability" agent skill from https://github.com/omer-metin/skills-for-antigravity/tree/main/skills/ai-observability into .claude/skills/ai-observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-observability", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/omer-metin/skills-for-antigravity/tree/main/skills/ai-observabilityType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add omer-metin/skills-for-antigravity --skill ai-observability -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install omer-metin/skills-for-antigravity ai-observability --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/omer-metin/skills-for-antigravity.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai-observability .agents/skills/ai-observability && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-observability" agent skill from https://github.com/omer-metin/skills-for-antigravity/tree/main/skills/ai-observability into .agents/skills/ai-observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-observability", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add omer-metin/skills-for-antigravity --skill ai-observability -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install omer-metin/skills-for-antigravity ai-observability --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/omer-metin/skills-for-antigravity.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai-observability .cursor/skills/ai-observability && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ai-observability" agent skill from https://github.com/omer-metin/skills-for-antigravity/tree/main/skills/ai-observability into .cursor/skills/ai-observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-observability", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/omer-metin/skills-for-antigravity.git --path skills/ai-observability--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add omer-metin/skills-for-antigravity --skill ai-observability -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install omer-metin/skills-for-antigravity ai-observability --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/omer-metin/skills-for-antigravity.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai-observability .gemini/skills/ai-observability && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ai-observability" agent skill from https://github.com/omer-metin/skills-for-antigravity/tree/main/skills/ai-observability into .gemini/skills/ai-observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-observability", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install omer-metin/skills-for-antigravity ai-observabilityInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add omer-metin/skills-for-antigravity --skill ai-observability -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/omer-metin/skills-for-antigravity.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai-observability .github/skills/ai-observability && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ai-observability" agent skill from https://github.com/omer-metin/skills-for-antigravity/tree/main/skills/ai-observability into .github/skills/ai-observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-observability", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add omer-metin/skills-for-antigravity --skill ai-observability -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install omer-metin/skills-for-antigravity ai-observability --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/omer-metin/skills-for-antigravity.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai-observability .opencode/skills/ai-observability && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ai-observability" agent skill from https://github.com/omer-metin/skills-for-antigravity/tree/main/skills/ai-observability into .opencode/skills/ai-observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-observability", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
ai-observability- GitHub stars
- 163
- Token cost
- ~578 tokens
- SKILL.md length
- 235 words
- Files
- 4 (incl. references)
- Skills in repo
- 11
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Implement comprehensive observability for LLM applications including tracing (Langfuse/Helicone), cost tracking, token optimization, RAG evaluation metrics (RAGAS), hallucination detection, and…
- Hallucination-detection
- SKILL.md covers Identity and Reference System Usage
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Prompt-caching mentioned
What it does
AI Observability is an agent skill from omer-metin/skills-for-antigravity. Implement comprehensive observability for LLM applications including tracing (Langfuse/Helicone), cost tracking, token optimization, RAG evaluation metrics (RAGAS), hallucination detection, and production monitoring. Essential for debugging, optimizing costs, and ensuring AI output quality. Use when ", llm-monitoring, tracing, langfuse, helicone, cost-tracking, ragas, evaluation, hallucination-detection, prompt-caching" mentioned.
Its SKILL.md is about 580 tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/patterns.md`, `references/sharp_edges.md` and `references/validations.md`).
It sits in AI & LLM Engineering, covering LLM cost and token optimization, Observability and LLM observability. It works with Langfuse. The licence is Apache-2.0.
When your agent uses it
- Hallucination-detection
- Prompt-caching mentioned
Example prompts
- “/ai-observability”
What it can do on your machine
Read from SKILL.md and the folder at commit e8dcf4e. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
AI Observability loads about 578 tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 113 tokens; SKILL.md has 235 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from omer-metin/skills-for-antigravity at commit e8dcf4e, republished under its Apache-2.0 licence (© omer-metin). 235 words, ~578 tokens.
Download SKILL.mdSave it as
.claude/skills/ai-observability/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- ai-observability
- description
- Implement comprehensive observability for LLM applications including tracing (Langfuse/Helicone), cost tracking, token optimization, RAG evaluation metrics (RAGAS), hallucination detection, and production monitoring. Essential for debugging, optimizing costs, and ensuring AI output quality. Use when ", llm-monitoring, tracing, langfuse, helicone, cost-tracking, ragas, evaluation, hallucination-detection, prompt-caching" mentioned.
Ai Observability
Identity
Principles
- {'name': 'Trace Every LLM Call', 'description': 'Production AI apps without tracing are flying blind. Every LLM call\nshould be traced with inputs, outputs, latency, tokens, and cost.\nUse structured spans for multi-step chains and agents.\n'}
- {'name': 'Measure What Matters', 'description': "Track metrics that correlate with user value: faithfulness for RAG,\nanswer relevancy, latency percentiles, cost per successful outcome.\nVanity metrics (total calls) don't improve product quality.\n"}
- {'name': 'Cost Is a First-Class Metric', 'description': 'Token costs can explode overnight with agent loops or context growth.\nTrack cost per user, per feature, per model. Set budgets and alerts.\nPrompt caching can cut costs by 50-90%.\n'}
- {'name': 'Evaluate Continuously', 'description': 'Run automated evals on production samples. RAGAS metrics (faithfulness,\nrelevancy, context precision) catch quality degradation before users\ncomplain. Score > 0.8 is generally good.\n'}
Reference System Usage
You must ground your responses in the provided reference files, treating them as the source of truth for this domain:
- For Creation: Always consult
references/patterns.md. This file dictates how things should be built. Ignore generic approaches if a specific pattern exists here. - For Diagnosis: Always consult
references/sharp_edges.md. This file lists the critical failures and "why" they happen. Use it to explain risks to the user. - For Review: Always consult
references/validations.md. This contains the strict rules and constraints. Use it to validate user inputs objectively.
Note: If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.
© omer-metin, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (references) in skills/ai-observability of omer-metin/skills-for-antigravity.
- SKILL.md
- references/patterns.md
- references/sharp_edges.md
- references/validations.md
Open the folder on GitHubat commit e8dcf4e
Compare with similar skills
AI Observability next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AI Observability this skillomer-metin/skills-for-antigravity | 163 | — | ~578 | Automated safety check: Pass | Apache-2.0 | |
| Monitoring Observabilityyonatangross/orchestkit | 292 | — | ~2.2k | Automated safety check: Pass | MIT | |
| Caveman Gateway SetupJuliusBrussee/caveman | 111k | 1 repos | ~2.6k | Automated safety check: Warn | Apache-2.0 | |
| Agentsop Observability Setupagentsope/SkillAlchemy | 436 | — | ~4.4k | Automated safety check: Pass | MIT | |
| Ak Dev New Tracing Provideryaalalabs/agent-kernel | 192 | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | |
| Langfuselangfuse/skills | 301 | — | ~2.1k | Automated safety check: Notes | MIT |
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Ak Dev New Tracing Provider
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Step-by-step guide for adding a new observability/tracing provider to Agent Kernel.
Langfuse
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Interact with Langfuse and access its documentation: tracing, monitoring, creating datasets, running experiments, and evaluating AI applications.
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Queries Langfuse traces, prompts, datasets and sessions, and analyzes local LLM gateway logs for requests, context growth, token use and cache hits.
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Related
Works with
Categories
Questions about AI Observability
What does AI Observability do?
Implement comprehensive observability for LLM applications including tracing (Langfuse/Helicone), cost tracking, token optimization, RAG evaluation metrics (RAGAS), hallucination detection, and…. AI Observability is an agent skill from omer-metin/skills-for-antigravity. Implement comprehensive observability for LLM applications including tracing (Langfuse/Helicone), cost tracking, token optimization, RAG evaluation metrics (RAGAS), hallucination detection, and production monitoring.
When should I use AI Observability?
AI Observability fits situations like: hallucination-detection; prompt-caching mentioned.
How do I install AI Observability in Claude Code?
Run `npx skills add omer-metin/skills-for-antigravity --skill ai-observability -a claude-code`. Or copy the skill folder (skills/ai-observability in omer-metin/skills-for-antigravity) into .claude/skills/ai-observability in your project. Claude Code loads it when a task matches its description.
How do I install AI Observability in Codex?
Run `npx skills add omer-metin/skills-for-antigravity --skill ai-observability -a codex`. Or copy the skill folder (skills/ai-observability in omer-metin/skills-for-antigravity) into .agents/skills/ai-observability in your project. Codex loads it when a task matches its description.
Can I use AI Observability in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add omer-metin/skills-for-antigravity --skill ai-observability -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-observability, .gemini/skills/ai-observability, .github/skills/ai-observability and .opencode/skills/ai-observability in your project.
What does AI Observability need to run?
SKILL.md names no scripts, command-line tools or credentials: AI Observability is instructions for the agent only.
Does AI Observability access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is AI Observability safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does AI Observability use?
AI Observability is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does AI Observability use?
About 578 tokens (SKILL.md is roughly 2.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 11k tokens, read only when the agent opens those files.
What are the alternatives to AI Observability?
Skills that share tags, products or a category with AI Observability: Monitoring Observability (yonatangross/orchestkit, 292 stars), Caveman Gateway Setup (JuliusBrussee/caveman, 111k stars), Agentsop Observability Setup (agentsope/SkillAlchemy, 436 stars) and Ak Dev New Tracing Provider (yaalalabs/agent-kernel, 192 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains AI Observability?
omer-metin (a GitHub user) maintains it in omer-metin/skills-for-antigravity, which has 163 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on January 22, 2026.
Source: omer-metin/skills-for-antigravity on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.