choose-observability-stack SKILL.md skillA
choose-observability-stack from contextjet-ai/awesome-llm-observability is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add contextjet-ai/awesome-llm-observability/choose-observability-stack@git:20261015.76d5de4Pins git:20261015.76d5de4 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- contextjet-ai/awesome-llm-observability
- Path
skills/choose-observability-stack/SKILL.md- Versions recorded
- 3
- Latest version
- git:20261015.76d5de4, committed Oct 15, 2026
- First version recorded
- Jul 5, 2026
- Size
- 3,365 bytes
- Repository stars
- 45
- License
- a license file GitHub does not identify
Use this to recommend an LLM observability / evaluation tool or stack for a specific situation. Trigger on "which observability tool should I use", "compare Langfuse vs Phoenix vs LangSmith", "what's the best LLM monitoring for us", or picking an eval/tracing/gateway tool given constraints (self-hosting, budget, compliance, existing stack). Ask about constraints, then recommend from the curated list - don't just name the most popular tool.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Choose an LLM observability stack There's no single best tool - the right choice depends on constraints. Gather them, then map to a recommendation. Base recommendations on this repo's curated list (verified tools + licenses), not on hype. ## Ask these constraints first 1. **Deployment**: SaaS OK, or must self-host / on-prem (data residency, regulated industry)? 2. **Primary need**: tracing/cost, *evaluation* (quality testing), or both? Prompt management too? 3. **Existing stack**: already on Datadog/Grafana/OTel? On LangChain? Using a gateway? 4. **Budget/licensing**: need a permissive OSS license (MIT/Apache), or is a commercial tier fine? (Note AGPL/Elastic-license implications for embedding.) 5. **Code-change tolerance**: want zero-code (proxy) or fine to add an SDK? 6. **Team**: engineers, or also non-technical PMs who need a UI? ## Map constraints → recommendation - **Must self-host, permissive license, want everything** → **Langfuse** (MIT core: tracing + evals + prompts) or **Comet Opik** (Apache-2.0). For eval-heavy local work, **Arize Phoenix**. …
Read the whole file at its exact version.
How to install
mdr add contextjet-ai/awesome-llm-observability/choose-observability-stack@sha256:4176e49a182b59b8The line at the top of this page pins the label git:20261015.76d5de4, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_zlrjgjteh7wkzpjl)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 3 versions of this file, between Jul 5, 2026 and Oct 15, 2026, about one every 51 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20261015.76d5de4 latest | 2026-10-15 | 76d5de4 | 3,365 B | A | view · diff |
| git:20260705.23078be | 2026-07-05 | 23078be | 3,340 B | A | view · diff |
| git:20260705.23977fd | 2026-07-05 | 23977fd | 3,346 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (3365 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
contextjet-ai/awesome-llm-observability · 45 stars · license a license file GitHub does not identify · pushed 2026-11-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_zlrjgjteh7wkzpjl GET https://markdownregistry.com/api/v1/resolve?ref=contextjet-ai/awesome-llm-observability/choose-observability-stack GET https://markdownregistry.com/api/v1/blob/4176e49a182b59b83fa427269ac296b9fa0985db739dab5b92d38c7c689370bb
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.