debugging-surveys

Write Streamlit app source code that runs well in a PostHog sandbox — the posthog_apps.query() bridge for reading PostHog data, the packages baked into the sandbox image, caching and session state across Streamlit reruns, layout and chart patterns, and the app.py entry point with any helper modules and data files bundled beside it. Use when authoring or debugging the Python source of a PostHog Streamlit app, when a query inside an app fails, or when asked to "write a streamlit app that shows PostHog data".

Write English that a reader cannot misread: one meaning per word, active voice, simple tenses, one idea per sentence, short sentences. Based on ASD-STE100 (Simplified Technical English), the controlled-language standard written for aircraft maintenance manuals. Use it for any prose an agent produces that someone else acts on. That covers reports and findings, PR descriptions and commit messages, instructions handed to another agent, tool descriptions, error messages, status summaries, and prompts. Also use it on request, with triggers like "simplify this", "make this readable", "too dense", "rewrite in STE", "simplified technical english", "ASD-STE100".

Read and use comments attached to the current PostHog task, its artifacts, and any canvas through the PostHog MCP exec dispatcher. Use when the user mentions task comments, artifact or canvas comments, annotations, selected-text feedback, replies, unresolved comments, or asks an agent to inspect or act on feedback left in PostHog Desktop. Covers exec discovery and calls, target filtering, pagination, full-thread retrieval, anchor/version context, task-scoped access, and standalone canvas comments that have no task.

Best practices for agents managing PostHog skills via the MCP `skill-*` tools — how to discover, read, create, update, and refactor skills efficiently, especially large skills with many bundled files. Use whenever you are about to call any `skill-*` tool, asked to author or edit a shared skill, or troubleshoot why a skill write was rejected. Also use when asked what skills are good for or how to shape one (project hub, runbook, catalog, handover, daily driver). Pairs with `skills-store` (which covers the raw tool surface) by adding the decision-tree, efficiency, pattern, and pitfall guidance.

Work with PostHog Signals scouts: scheduled agents that monitor a project and write reports into the Signals inbox. Use to assign monitoring work, schedule quality scoring, find which scout covers a surface, act on reports, reduce noise, investigate missing findings, or improve the fleet through feedback and calibration. Also covers follow-up checks that verify whether a reported problem stays fixed. Use `authoring-scouts` for edits, `exploring-scouts` for run observability, and `inbox-exploration` for report triage. Trigger on "work with my scouts", "get more out of scouts", "have a scout watch X", "tell me if Y spikes", "score X on a schedule", "measure quality of Y", "what do I do with this scout report", "calibrate/review my scout fleet".

Use PostHog Autoresearch, agent-driven predictive models: ask "who will do X in the next N days?", let an agent train a model, then score people daily into a person property and `autoresearch_prediction` events. Use when a user wants to predict churn, activity, return, feature adoption, conversion or any event or action per person; create or validate a model from a template; start training or score now; read model quality (holdout vs realized AUC, lift, calibration, likelihood segments, coverage); steer training with suggestions; act on predictions with cohorts, feature flags, workflows or SQL; or diagnose a model that fails to train, scores everyone the same, or stops scoring. Trigger on "autoresearch", "predictive model", "propensity score", "churn prediction", "likely to convert", "who will do X", "predicted_p_", "autoresearch_prediction", "realized AUC", "champion model".

Validate and publish a canvas source project safely: the source-project shape, declared capabilities, reading the current version pointer, iterating on validation diagnostics, guarded publishing with expected_current_version_id, staging a draft build and promoting it, waiting out the queued build, and recovering from a 409 version_conflict or a 429 capacity limit without overwriting concurrent work. Use whenever a canvas edit is ready to save, a draft build is wanted, a canvas publish or build returns diagnostics or a conflict, or a task needs to understand canvas version history.

Explains PostHog billing usage and spend from the customer's visible Billing MCP tools. Use when the user asks why usage or spend is high, which product or project is driving usage, what a usage type means, how to reduce usage, what changed over time, why they got a usage change alert, or whether a spike/drop alert was real or noisy. Also use before product-specific analytics skills when the user names a billable PostHog product metric such as events, recordings, feature flag requests, exceptions, survey responses, synced rows, logs, AI events, AI credits, or Inbox credits. Starts from Billing usage/spend tools, then routes to customer-visible product MCP surfaces for deeper investigation.

Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.

No description in the SKILL.md.

Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices".

tasteskill 2.5.1, the anti-slop frontend skill. Builds professional company websites at the level of figma.com and x.ai: plain copy in a voice of its own, one system, one section per screen, equal edges, real photographs and real product UI (licensed stand-in photographs when the client has none; a product render only when the brief asks for 3D), a hero entrance and one or two dealt moments on every page, shader effects and scenes only on tech, gaming and software pages, quiet micro-interactions, and a checker and finish gate that enforce it in a real browser. Use this whenever you build, design, redesign, restyle, polish or review a landing page, company, product, shop, cafe, hotel, studio, SaaS, AI, developer-tool or game site, as static HTML/CSS or inside an existing React, Next.js, Vue, Svelte, Astro or Tailwind project, or when the user says a page looks generic, templated or "AI-made".

React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.

UI/UX design intelligence for web, mobile, and desktop. This skill should be used when designing, building, reviewing, or fixing interfaces, including pages, components, design systems, accessibility, interaction, responsive layout, typography, color, charts, and stack-specific UI implementation. Searchable local data: 80 searchable styles (51 active), 192 product palettes and reasoning profiles, 74 font pairings, 120 UX guidelines, 105 icons, 17 GSAP presets, 25 chart types, and 22 stacks.