meta-kid-project-planner
The meta-kid-project-planner skill transforms a child's project idea into dual-audience guidance: a step-by-step plan for the child and a parent-facing supervision pack that includes feasibility assessment, age-appropriate materials with budget alternatives, and safety considerations. Use it when a child or guardian proposes a school project, science fair entry, hobby kit, or creative venture like a volcano model or bug-watching channel, ensuring the plan matches the child's age and refuses unsafe or inappropriate projects.
git clone --depth 1 https://github.com/opensquilla/opensquilla /tmp/meta-kid-project-planner && cp -r /tmp/meta-kid-project-planner/src/opensquilla/skills/bundled/meta-kid-project-planner ~/.claude/skills/meta-kid-project-plannerSKILL.md
# meta-kid-project-planner Junior & guardian persona meta-skill. Turns a child's project idea — "我要做火山", "I want to build a model rocket", "open a YouTube channel about insects" — into a kid-friendly step plan PLUS a parent-friendly oversight pack. The two audiences are concatenated in one markdown deliverable with clear `## 👦 For You (the kid)` / `## 👨👩👧 For the Grown-up` sections — a markdown-level workaround for the proposed `audience:` primitive (portfolio design §4.2). ## Composition philosophy — multi-skill bundled orchestration This meta-skill uses **only OpenSquilla-bundled atomic skills** plus the five built-in step kinds — no external dependencies. The DAG calls into **5 distinct bundled atomic skills**: | Skill | Step(s) | Role in the DAG | |---|---|---| | `multi-search-engine` | `web_research` | Find existing how-to guides for the topic | | `deep-research` | `deep_research` | Extra round for `SAFETY_REVIEW_REQUIRED` or `NEEDS_SHOPPING` feasibility | | `memory` | `recall_past_projects`, `store_project` | Per-child memory: what they've already done; what they did this time. Avoids project repeats and builds a learning trajectory. | | `weather` | `weather_check` | When the topic is outdoor / garden / park, pull a 7-day forecast so `outline_steps` can recommend the best day | | `pptx` | `kid_deck` | When `PARENT_SUPERVISION: HANDS_ON`, produce a printable slide deck for the kid (visual step-by-step + safety callouts) | Step kinds used: `llm_chat`, `llm_classify`, `user_input`, `skill_exec`, `agent`. Vocab card generation is a plain `llm_chat` step (`vocab_cards`) grounded in `outputs.outline_steps + outputs.material_list` — the LLM produces 6 age-appropriate cards directly. No external flashcard skill is required. Bilingual rendering for `LANGUAGE: mixed` is also prompt-side in the relevant steps — no separate translation skill required. ## Safety design Three layers of guardrail: 1. `preferences` step rejects clearly inappropriate topics by setting `PROJECT_SAFE: no` in its contract. This is prompt-side; cannot be bypassed by clever phrasing because the model's response is constrained to the return format. 2. `feasibility` classifier produces `INAPPROPRIATE` for any topic that involves weapons, dangerous chemistry, fire-without-adult, self-harm-adjacent themes. `INAPPROPRIATE` short-circuits the project pack and routes to `redirect_unsafe`. 3. `redirect_unsafe` produces a gentle, non-shaming redirect with 3 alternative project ideas that scratch the same itch safely. The skill never silently degrades safety — if the topic is unsafe, the deliverable IS the redirect, with `PACK_DELIVERED: no_safety_redirect`. ## Honest limitations (first-wave) - **`audience:` is markdown sections, not real two-principal output.** When the proposed primitive ships, the kid section can go to a child-facing surface while the parent section goes to the guardian's channel, separately. - **No persistence of past projects.** Each invocation is independent — without `state:`, the skill cannot remember which projects the child has already done. - **Vocab cards do not feed an FSRS deck.** The `vocab_cards` step emits a one-shot card list; integrating with a spaced-repetition state machine is reserved for a future `meta-spaced-rep-coach`. - **Topic safety relies on prompt-side guardrails.** A future dedicated safety-policy step kind would be more robust than prompt-side judgment under adversarial inputs.
Submit audio or video for multilingual dubbing, poll status, and download dubbed audio. Use when the user asks for dubbing, 多语言配音, 视频翻译配音, 译制片, or wants a source clip dubbed into another language.
Generate a structured short-video shooting script from a topic. Emits a strict, machine-parseable shot list (3 shots by default) with image prompt + video prompt + voiceover + on-screen text per shot. Trigger when the user asks for a video script, 分镜, 短视频文案, AI视频, 短剧脚本, or wants visual prompts ready for image/video generation.
Use when the user asks to schedule recurring tasks, one-off reminders, timers, or cron-style jobs through the OpenSquilla cron tool.
Multi-round research with explicit methodology, evidence tracking, and citation-tagged synthesis. Trigger on 'deep dive', 'research report', 'literature review', 'investigate X across sources', 'multi-round investigation'. Distinct from the `summarize` skill, which is a single-pass condensation; this skill maintains a state file across iterations, tracks coverage, and produces a long-form report with per-claim citations. Three execution stages: plan (scope into sub-questions), iterate (record evidence per round), compile (synthesize report). The skill itself does not fetch the web — it tells the host agent which fetches to perform via OpenSquilla's existing web tools, and records what comes back.
Read, edit, or create Microsoft Word `.docx` files. Trigger this skill whenever the user mentions a Word document, .docx file, contract, report, brief, memo, or asks to extract text, modify an existing doc, generate one from a brief, or audit tracked changes. Three execution paths: text-and-structure extraction, in-place edit-by-run (preserves styles), and create-from-scratch with python-docx. Falls back to OOXML unzip-and-patch for layout work python-docx cannot reach.
Capture the current git diff (staged, working-tree, or staged file list) as text. Direct shell call for workflows that need repository diffs without an LLM agent loop.
GitHub operations via `gh` CLI: issues, PRs, CI runs, code review, API queries. Use when: (1) checking PR status or CI, (2) creating/commenting on issues, (3) listing/filtering PRs or issues, (4) viewing run logs. NOT for: complex web UI interactions requiring manual browser flows (use browser tooling when available), bulk operations across many repos (script with gh api), or when gh auth is not configured.
Query the per-turn DecisionEntry log for skill co-occurrence patterns, meta-skill usage stats, and the router fixture corpus. Returns a JSON summary suitable for downstream LLM consumption. Used by meta-skill-creator's harvest step but also useful standalone for 'which skills did I use most this week?'