session-review

How to structure A vs B comparisons in Fullstory — when to use dimensionality (event/session properties) vs separate segments (user-level properties), and why the distinction matters for correctness.

Finds where users struggle on a page or flow and whether a suspected problem is real. Ranks Fullstory's frustration and error signals, separates real problems from buttons people are meant to click many times, measures how many users each problem affects, and uses session replays to show what happened. Use when someone asks where users are struggling, what is broken on a page or flow, for top pain points or a friction audit, why users give up at a step, whether a rage click is real, whether pages feel slow, whether people keep retrying, re-typing or going back and forth, whether a mobile app keeps crashing, or whether a problem from support tickets is widespread or affects only a few people.

Fullstory analytics workflow — the default way to answer any question about user behavior. Use whenever someone asks how many, what percentage, which pages, whether something is trending, where users drop off, what users did before or after an action, or how two cohorts compare — and also when they describe a business question that needs numbers behind it without ever saying "metric", "funnel", or "segment". Covers building and computing metrics, segments, funnels, and journeys, verifying that what got built is what was actually asked for, and pulling sessions to explain why the numbers look the way they do. Not for reviewing one specific session, or for setting up capture and instrumentation.

Finds product improvement ideas a team has not already considered. Searches the metrics, segments and funnels the team already built, builds the ones that are missing, measures how many users each idea affects against a baseline, and pulls session replays as evidence. Returns 3 to 5 ranked proposals, each with what is new about it, a user count with its baseline, and replay links. Use when someone asks what to build next, how to improve a product area or flow, what the team is missing, for data-backed product ideas or proposals, or what changed after a release. If the user only wants the list of Fullstory Opportunities, call the Opportunities tools directly instead. For counts, rates and trends use general-analysis, for A vs B mechanics use comparisons, and for one session use session-review.

Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.

Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".

Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.

This skill should be used when the user wants to "write agent code", "build an agent with ADK", "add a tool", "create a callback", "define an agent", "use state management" — in a project that needs ADK (Agent Development Kit) API patterns and code examples. It provides a quick reference for agent types, tool definitions, orchestration patterns, callbacks, state management, the graph Workflow API, and reference recipes to study. Do NOT use for scaffolding (use google-agents-cli-scaffold) or deployment (use google-agents-cli-deploy).

Set up Claude Code hooks to block dangerous git commands (push, reset --hard, clean, branch -D, etc.) before they execute. Use when user wants to prevent destructive git operations, add git safety hooks, or block git push/reset in Claude Code.

Generate AI music on RunComfy via the `runcomfy` CLI — a smart router across the music-model catalog. Routes to ElevenLabs AI Music Generation (premium 44.1 kHz stereo vocal tracks, 5 s–5 min, $0.0083/s) and ACE Step / ACE Step 1.5 (StepFun-AI open-weights, tag-driven composition, multilingual lyrics, $0.0002–0.0003/s, ~27× cheaper), plus ACE Step audio-inpaint (regenerate a time range inside an existing track) and ACE Step audio-outpaint (extend a track before or after). Picks the right model for the user's actual intent — premium vocal hook, cheap background music library, multilingual pop song, repair a bad chorus, lengthen a 30 s draft into a 2 min cut — and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "generate music", "make a song", "AI music", "background music", "instrumental track", "soundtrack", "jingle", "theme music", "royalty-free music", "compose", "music with lyrics", "extend music", "fix this song", "inpaint music", or any explicit ask to generate or edit music.

创建 lark-cli 的自定义 Skill。当用户需要把飞书 API 操作封装成可复用的 Skill（包装原子 API 或编排多步流程）时使用。