penguin-harness/changelog/0.1.0/2026-07-20-skills.md

Skill library and the AI-app skills

One-shot RAG app flow: skills rewrite and a draft-screen example task

PR #11's squash — briefly lost to a force-push race during the branch rebase — is restored: the skills library rewrite that makes one-sentence RAG apps one-shot, a draft-screen example task card, and the finished-product showcase pipeline.

• penguin-sdk rewritten around a complete RAG recipe (corpus collection, heading chunking, local BM25 retrieval, per-request Session SSE answers with citations, run-and-verify checklist); web-design gains the Penguin visual language and chat/RAG layout recipes; agent-creation covers skill bundles; agenthub-dev retires and a firecrawl skill joins.
• The Web draft screen gains example task cards (full prompts submitted as-is), with chat stream rendering refinements (markdown module, work summaries, stream follow) and colorful skill icons.
• The landing capture pipeline drives the docs-expert conversation and renders the finished-app mockup; README/Cases assets and prompts match the earlier finished-product switch.

Skill library regrouped by audience, with square card actions

The library's six ad-hoc groups become four audience-oriented ones, and the card actions move into a tidy column.

• New groups, in order: Office Productivity / 办公效率 (data-analysis, firecrawl), Software Development / 软件开发 (web-design, software-engineering), AI App Development / AI 应用开发 (penguin-sdk, penguin-cli, agenthub-models), and Agent Tuning / Agent 调优 (agent-creation, benchmark-design, agent-evaluation, agent-optimization). Docs tables, skills/server tests, and the skills e2e spec follow.
• Skill card actions (update nudge / quick invoke / manage installs) are now equal squares stacked in one column, vertically centered at the card's right edge; the metadata line moves under the header.

Skills: pin the CLI --root to the app dir and fast-stop when no key

Three skills gain two hard rules for AI-app development: always target the app's own data root with the penguin CLI, and stop asking for help the moment no API key is usable.

• penguin-sdk (v7), agenthub-models (v4), penguin-cli (v2): when building an AI app, penguin config ... must always pass --root <data_dir> pointing at the app's data directory inside the current working directory (the same path given to createAgent({ root }), e.g. ./penguin_data); running without --root writes to the global ~/.penguin/data, which belongs to the person running Penguin, not the app.
• penguin-sdk (v7) and agenthub-models (v4): when no API key is usable, stop immediately and ask the user for help instead of looping on tool calls — re-running env, re-checking the vault, or retrying the build wastes turns and money; one clear check, then hand back to the user (open the agent's settings via the gear icon and add a key to the key vault).

System prompt exposes Provider and Model ID; skills state the key-first premise

The Agent system prompt's Environment section now carries the session model reference, and the AI-app skills spell out the key-and-root prerequisites up front.

• The # Environment section gains Provider: {{PROVIDER}} and Model ID: {{MODEL_ID}} placeholders (the session model's provider group and upstream id, filled from the resolved model entry) right before Session ID, and the fields are reordered to Project Dir → Agent ID → CWD → Provider → Model ID → Session ID. assembleSystemPrompt / SessionEnvironmentValues / sessionEnvironment thread the two new values through; the configuration docs' placeholder table (en/zh) follows.
• penguin-sdk (v8) and agenthub-models (v5) open with the prerequisite: for AI-app development, have the user add the model API key in this agent's key vault before building, and keep the app's Penguin data root inside the CWD workspace (--root ./penguin_data), never ~/.penguin; model ids can come from the penguin CLI catalog.