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creating-online-evaluations

Author continuously-running online evaluations in PostHog AI observability, grounded in real failure modes you've identified.

Skill by PostHogOfficial

IndexedLicense unknown★ 95
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/posthog-creating-online-evaluations

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Author continuously-running online evaluations in PostHog AI observability, grounded in real failure modes you've identified. Use when the user wants evaluations that automatically score new generations or whole traces going forward — "create an eval to catch X", "continuously check that responses do Y", "turn these failures into evals". Covers letting the explored data decide how many evals to create, proposing that set for the user to pick, choosing the target and eval type (hog / llm_judge / sentiment), configuring a provider and model for an llm_judge eval (a provider key gates enabling, not creation), scoping which generations trigger it via conditions, creating disabled, verifying scope, enabling, and backfilling past data. Proposes a sentiment eval when no failure mode is worth catching. Finding and ranking the failure modes worth evaluating is its own job — use exploring-ai-failures first. To debug or manage evaluations that already exist, use exploring-llm-evaluations.

Use cases: data, ml

Reviews

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/creating-online-evaluations

What's inside

Skill name
creating-online-evaluations
Description
Author continuously-running online evaluations in PostHog AI observability, grounded in real failure modes you've identified. Use when the user wants evaluations that automatically score new generations or whole traces going forward — "create an eval to catch X", "continuously check that responses do Y", "turn these failures into evals". Covers letting the explored data decide how many evals to create, proposing that set for the user to pick, choosing the target and eval type (hog / llm_judge / sentiment), configuring a provider and model for an llm_judge eval (a provider key gates enabling, not creation), scoping which generations trigger it via conditions, creating disabled, verifying scope, enabling, and backfilling past data. Proposes a sentiment eval when no failure mode is worth catching. Finding and ranking the failure modes worth evaluating is its own job — use exploring-ai-failures first. To debug or manage evaluations that already exist, use exploring-llm-evaluations.
License
unknown
Instructions
421 lines in SKILL.md · view on GitHub

Files (2)

  • SKILL.md
  • evaluation-payload.md · references/

The license isn't open source, so the instructions aren't shown here. Read SKILL.md on GitHub

More from PostHog/ai-plugin

Signals

Stars
95
Forks
20
Open issues
12
Last commit (this folder)
Oct 23, 2026 (5 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
License unknown
Repository
github.com/PostHog/ai-plugin
First seen
Oct 24, 2026
Last checked
Oct 24, 2026
Source
GitHubgithub-graphql

Same skill elsewhere

Copies of this SKILL.md published by others; search shows only one of them.

More from PostHog

Cite this page

creating-online-evaluations skill. Agent Mart. https://agentmart.dev/skills/posthog-creating-online-evaluations (last updated 2026-10-24)