Langfuse Integration Page
langfuse/langfuse-docs
Create a new Langfuse integration page in the langfuse-docs repo.
Prepare Langfuse weekly production reviews covering failures, fixes, open issues, and tracking gaps.
Install Weekly Production Review
$ npx skills add langfuse/langfuse --skill weekly-production-review -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install langfuse/langfuse weekly-production-review --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/langfuse/langfuse.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/weekly-production-review .claude/skills/weekly-production-review && 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 "weekly-production-review" agent skill from https://github.com/langfuse/langfuse/tree/main/.agents/skills/weekly-production-review into .claude/skills/weekly-production-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "weekly-production-review", 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/langfuse/langfuse/tree/main/.agents/skills/weekly-production-reviewType 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 langfuse/langfuse --skill weekly-production-review -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install langfuse/langfuse weekly-production-review --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/langfuse/langfuse.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/weekly-production-review .agents/skills/weekly-production-review && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "weekly-production-review" agent skill from https://github.com/langfuse/langfuse/tree/main/.agents/skills/weekly-production-review into .agents/skills/weekly-production-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "weekly-production-review", 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 langfuse/langfuse --skill weekly-production-review -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install langfuse/langfuse weekly-production-review --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/langfuse/langfuse.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/weekly-production-review .cursor/skills/weekly-production-review && 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 "weekly-production-review" agent skill from https://github.com/langfuse/langfuse/tree/main/.agents/skills/weekly-production-review into .cursor/skills/weekly-production-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "weekly-production-review", 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/langfuse/langfuse.git --path .agents/skills/weekly-production-review--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 langfuse/langfuse --skill weekly-production-review -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install langfuse/langfuse weekly-production-review --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/langfuse/langfuse.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/weekly-production-review .gemini/skills/weekly-production-review && 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 "weekly-production-review" agent skill from https://github.com/langfuse/langfuse/tree/main/.agents/skills/weekly-production-review into .gemini/skills/weekly-production-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "weekly-production-review", 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 langfuse/langfuse weekly-production-reviewInstalls 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 langfuse/langfuse --skill weekly-production-review -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/langfuse/langfuse.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/weekly-production-review .github/skills/weekly-production-review && 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 "weekly-production-review" agent skill from https://github.com/langfuse/langfuse/tree/main/.agents/skills/weekly-production-review into .github/skills/weekly-production-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "weekly-production-review", 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 langfuse/langfuse --skill weekly-production-review -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install langfuse/langfuse weekly-production-review --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/langfuse/langfuse.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/weekly-production-review .opencode/skills/weekly-production-review && 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 "weekly-production-review" agent skill from https://github.com/langfuse/langfuse/tree/main/.agents/skills/weekly-production-review into .opencode/skills/weekly-production-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "weekly-production-review", 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
weekly-production-review- GitHub stars
- 36k
- Token cost
- ~4.1k tokens
- SKILL.md length
- 2,099 words
- Files
- 2
- Skills in repo
- 33
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Prepare Langfuse weekly production reviews covering failures, fixes, open issues, and tracking gaps.
- Works in 9 steps: Confirm the review window and timezone.… → Gather public/customer-facing incidents… → Gather incident.io alert load for the… → …
- What broke last week
- SKILL.md covers Scope, Related Skills, Workflow and Output Contract, plus 7 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Weekly Production Review is an agent skill from langfuse/langfuse. Prepare Langfuse weekly production reviews covering failures, fixes, open issues, and tracking gaps. Use for "what broke last week," production bugs, Datadog alerts or error patterns, incident.io activity, or pager load.
Its SKILL.md is about 4.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).
It sits in AI & LLM Engineering, covering LLM observability. It works with Langfuse and Datadog. The repository describes itself as: 🪢 Open source agent evals & observability: Trace, evaluate, and improve LLM applications with one open platform.
When your agent uses it
- What broke last week
- Production bugs
- Incident.io activity
Example prompts
- “what broke last week,”
- “/weekly-production-review”
Workflow steps
9 steps, taken from the first numbered list in SKILL.md.
- Confirm the review window and timezone. If the user says "last week", use the
- Gather public/customer-facing incidents from incident.io. Prefer incident.io
- Gather incident.io alert load for the same review window. Prefer
- Gather Linear bugs from the bug label first. Include all bug-labeled
- Gather Datadog alert/page signals for the window. Use incident.io alerts or
- For every Datadog alert/page cluster, perform the deep dive before writing the
- Gather Datadog error log patterns for the window. Use logs with
- Classify each incident, bug, alert, alert-load row, and log pattern. Separate
- Cross-reference source rows on a best-effort basis. Link Datadog rows to
What it can do on your machine
Read from SKILL.md and the folder at commit eecc7d0. 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
Weekly Production Review loads about 4.1k tokens when it runs. Until then it costs about 61 tokens; SKILL.md has 2,099 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
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 2,099 words (~4,059 tokens).
“Use this skill to produce a source-grounded production review across Datadog, incident.io, and Linear. Keep the output factual, table-first, and easy to audit from the linked source rows.”
- name
- weekly-production-review
Files
SKILL.md and 1 other file in .agents/skills/weekly-production-review of langfuse/langfuse.
- SKILL.md
- agents/openai.yaml
Open the folder on GitHubat commit eecc7d0
Compare with similar skills
Weekly Production Review 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 |
|---|---|---|---|---|---|---|
| Weekly Production Review this skilllangfuse/langfuse | 36k | — | ~4.1k | Automated safety check: Pass | Custom licence | |
| Langfuse Integration Pagelangfuse/langfuse-docs | 246 | — | ~3.7k | Automated safety check: Pass | MIT | |
| Langfuselangfuse/skills | 301 | — | ~2.1k | Automated safety check: Notes | MIT | |
| Add Yourself To Team Langfuselangfuse/langfuse-docs | 246 | — | ~548 | Automated safety check: Pass | MIT | |
| Ag2 Telemetryag2ai/build-with-ag2 | 252 | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| LangfuseAnil-matcha/awesome-muse-connectors | 1.3k | — | ~773 | Automated safety check: Pass | MIT |
Similar skills
Langfuse
langfuse/skills
Interact with Langfuse and access its documentation: tracing, monitoring, creating datasets, running experiments, and evaluating AI applications.
Add Yourself To Team Langfuse
langfuse/langfuse-docs
Add a new team member to Langfuse's canonical team data and shared team table.
Ag2 Telemetry
ag2ai/build-with-ag2
Add OpenTelemetry traces to an AG2 beta Agent via TelemetryMiddleware (autogen.beta.middleware.builtin).
Langfuse
Anil-matcha/awesome-muse-connectors
Read and write Langfuse: browse traces and observations, list prompts and datasets, score traces, add dataset items.
Langfuse Data Handling
jeremylongshore/tons-of-skills-marketplace
Manage Langfuse data export, retention, and compliance requirements.
More from langfuse/langfuse
All 33 skills in this repoLinear Context Handover
langfuse/langfuse
Use Linear as the org's memory: reconstruct a feature's history before touching it, and leave the reasoning behind finished work in the ticket description so the next agent inherits it.
Add Model Price
langfuse/langfuse
A skill your agent uses when editing worker/src/constants/default-model-prices.json, packages/shared/src/server/llm/types.ts, pricing tiers, tokenizer IDs, or matchPattern regexes for OpenAI…
Backend Dev Guidelines
langfuse/langfuse
Build or review Langfuse backend code. An agent skill from langfuse/langfuse.
Langfuse Codebase Navigator
langfuse/langfuse
Navigate Langfuse repositories, code areas, and agent skills.
Refactor React Effects
langfuse/langfuse
Refactor avoidable React useEffect usage in Langfuse frontend code.
Add To Dependabot CSV
langfuse/langfuse
Append GitHub Dependabot or Snyk/code-scanning alerts to an existing vulnerability CSV after verifying their API metadata.
Related
Categories
Questions about Weekly Production Review
What does Weekly Production Review do?
Prepare Langfuse weekly production reviews covering failures, fixes, open issues, and tracking gaps. Weekly Production Review is an agent skill from langfuse/langfuse. Prepare Langfuse weekly production reviews covering failures, fixes, open issues, and tracking gaps.
When should I use Weekly Production Review?
Weekly Production Review fits situations like: what broke last week; production bugs; incident.io activity.
How do I install Weekly Production Review in Claude Code?
Run `npx skills add langfuse/langfuse --skill weekly-production-review -a claude-code`. Or copy the skill folder (.agents/skills/weekly-production-review in langfuse/langfuse) into .claude/skills/weekly-production-review in your project. Claude Code loads it when a task matches its description.
How do I install Weekly Production Review in Codex?
Run `npx skills add langfuse/langfuse --skill weekly-production-review -a codex`. Or copy the skill folder (.agents/skills/weekly-production-review in langfuse/langfuse) into .agents/skills/weekly-production-review in your project. Codex loads it when a task matches its description.
Can I use Weekly Production Review 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 langfuse/langfuse --skill weekly-production-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/weekly-production-review, .gemini/skills/weekly-production-review, .github/skills/weekly-production-review and .opencode/skills/weekly-production-review in your project.
What does Weekly Production Review need to run?
SKILL.md names no scripts, command-line tools or credentials: Weekly Production Review is instructions for the agent only.
Does Weekly Production Review 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 Weekly Production Review 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 Weekly Production Review use?
Weekly Production Review has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Weekly Production Review use?
About 4.1k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Weekly Production Review?
Skills that share tags, products or a category with Weekly Production Review: Langfuse Integration Page (langfuse/langfuse-docs, 246 stars), Langfuse (langfuse/skills, 301 stars), Add Yourself To Team Langfuse (langfuse/langfuse-docs, 246 stars) and Ag2 Telemetry (ag2ai/build-with-ag2, 252 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Weekly Production Review?
langfuse (a GitHub organization) maintains it in langfuse/langfuse, which has 35,586 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 10, 2026.
Source: langfuse/langfuse on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.