com um clique
bmad-idea
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Baseado na classificação ocupacional SOC
Assist with Colibri: pure-C LLM inference engine for running GLM-5.2 (744B MoE) on consumer machines with ~25 GB RAM. Use when setting up, building, converting models, running inference, configuring expert streaming and caching, optimizing speculative decoding (MTP), GPU integration, and integrating Colibri into production pipelines. Includes build setup, model download & conversion, chat/inference modes, performance tuning, and API integration patterns.
Discover and apply curated prompts from the prompts.chat collection to optimize AI interactions. Use when refining prompt engineering, finding domain-specific prompt templates, improving response quality, or building prompt-based workflows. Triggers on: prompt optimization, prompt templates, prompt engineering, prompt library, curated prompts, prompt discovery, and AI prompt patterns.
Turn ONE topic into a finished Vox-style paper-collage explainer / ad video, end to end on the Atlas Cloud API + local ffmpeg — script, collage keyframes, motion, voice-over, music, captions, all automated. Use this whenever the user wants a "Vox style" video, a paper/torn-paper collage animation, a "motion collage", a narrated explainer or short ad built from AI-generated collage posters, a scrapbook-style tribute, or wants to turn a topic / product / person into a punchy narrated collage video — even if they don't say the word "Vox". Also use when reproducing Stav Zilber / rom1trs / Higgsfield-style collage ad workflows, or when the user asks for a motion collage or a scrapbook-style tribute. Triggers: "vox video", "collage video", "motion collage", "paper collage explainer", "make a collage ad", "turn this topic into a collage video".
Assist with Motion Previs Studio v4: a cross-platform desktop app for AI-film previsualization. Use when setting up, configuring, troubleshooting, or extending motion-previs-studio for pose extraction, depth mapping, camera motion solving, control layer export, and bundle production for AI-video workflows (Seedance, ComfyUI, Blender, Runway, Kling). Includes build setup, feature integration, UI/logic debugging, and export pipeline optimization.
Work with Lapian Notes / 拉片笔记 (github.com/bkingfilm/lapian-notes) — a local- first React/Vite tool that turns a film into an editable shot-by-shot study notebook: local frame extraction, AI-assisted structure analysis (bring your own AI, no API key required), story-line swimlane timeline, structure tree, and audience-emotion curve. Use when the user asks about Lapian Notes, "拉片笔记", "拉片" (shot-by-shot film analysis) tooling, cloning/running this repo (npm run dev, run.bat/run.command), the AI-analysis-package (ZIP) round-trip workflow, or contributing a PR to lapian-notes. Not for generic video editing (use `opencut` for that) or generic film-analysis theory unrelated to this codebase.
Set up, run, and contribute to TokHub (github.com/yaojingang/TokHub) — an open-source AI API relay monitoring, recommendation, and OpenAI-compatible gateway system with L1/L2/L3 channel health probing, usage metering, alerts, audit, and Docker self-hosting. Use when the user asks about TokHub, "AI API 中转站监控", cloning/running the Go + React monorepo (TOKHUB_ROLE, sqlc, TimescaleDB, NATS), the L1/L2/L3 probe algorithm, the OpenAI-compatible `/gateway/v1/*` endpoint, or contributing a PR to TokHub. Do not use for connecting a running agent to a live TokHub instance's own API (that is covered by the project's own bundled `agent-skills/tokhub` skill inside the TokHub repo, not this one).
| name | bmad-idea |
| description | > |
| compatibility | > |
| allowed-tools | Read Write Bash Grep Glob |
| metadata | {"tags":"bmad, ideation, concept-design, problem-framing, positioning, storytelling, product-discovery, game-concept, creative-routing","platforms":"Claude, Gemini, Codex, OpenCode","keyword":"bmad-idea","version":"2.0.0","source":"akillness/jeo-skills"} |
Use this skill as the repository's pre-planning creative intake and concept-routing layer.
The job is not to dump dozens of ideation techniques or persona gimmicks. The job is to:
Read references/operating-modes.md for mode-selection heuristics, references/handoff-boundaries.md for adjacent-skill routing, and references/concept-packet-template.md for reusable output scaffolding.
bmad-gds or task decompositionbmadtask-planningmarketing-automationbmad-gdsChoose exactly one primary mode per run.
Problem framing
Audience and value framing
Concept shaping
Game concept framing
bmad-gdsStory packaging
Capture the packet in this format before choosing a mode:
idea_packet:
domain: product | gtm | content | consulting | game | mixed | unknown
stage: raw-idea | rough-concept | candidate-offer | concept-with-notes | narrative-draft | unknown
audience:
primary_user: "who this is for"
pains_or_needs:
- pain 1
- pain 2
problem_or_goal: "what change or outcome is this idea trying to create?"
current_material:
- notes
- brainstorm bullets
- positioning draft
- customer research
- game concept notes
- moodboard / references
- pitch / story draft
strongest_unknown: problem | audience | value | concept-scope | game-pillars | narrative | unknown
downstream_target: bmad | task-planning | marketing-automation | bmad-gds | deck | unknown
constraint: time | scope | evidence | differentiation | alignment | unknown
If the packet is incomplete, continue with explicit assumptions instead of stalling.
Select the mode that reduces ambiguity fastest.
| If the biggest gap is... | Choose... | Primary output |
|---|---|---|
| We do not yet know what problem is worth solving | Problem framing | problem brief |
| We do not know for whom this idea matters or why it is better | Audience and value framing | positioning brief |
| We have too many half-ideas and need one tighter concept | Concept shaping | concept brief |
| We need to define fantasy, pillars, loop, and hook for a game | Game concept framing | game concept packet |
| The idea exists but people do not understand or support it yet | Story packaging | story / pitch packet |
Do not mix multiple modes unless the user explicitly asks for a two-pass workflow.
Return exactly one primary artifact:
problem briefpositioning briefconcept briefgame concept packetstory / pitch packetThe artifact should be concise, reusable, and ready to hand to a downstream skill.
When the concept artifact is done, recommend the next downstream lane if appropriate:
bmad → when the next job is phase routing and selecting PRD / tech spec / architecture / sprint-plan depthtask-planning → when the concept is approved and needs backlog slices, milestones, or execution packetsmarketing-automation → when the concept is sound and now needs launch, messaging operations, campaign structure, or KPI-aware marketing follow-throughbmad-gds → when the game concept is strong enough to turn into milestones, GDD slices, playtest planning, or production coordinationAlways state why that route-out is next and what packet should be passed forward.
# Idea Routing Brief
## Scope
- Domain: ...
- Stage: ...
- Strongest unknown: ...
- Downstream target: ...
- Confidence: high | medium | low
## Chosen mode
- problem-framing | audience-and-value-framing | concept-shaping | game-concept-framing | story-packaging
## What matters most now
- 2-4 bullets grounded in the packet
## Recommended artifact
- problem brief | positioning brief | concept brief | game concept packet | story / pitch packet
## Artifact contents
| Section | Decision | Why it matters now |
|---------|----------|--------------------|
| ... | ... | ... |
## Immediate next steps
1. ...
2. ...
3. ...
## Route-outs
- Skill / workflow: ...
- Why next: ...
- What to pass forward: ...
## What not to do yet
- 1-3 bullets preventing premature planning, launch detail, or execution drift
Good outputs are short enough to reuse.
Guardrails:
Older BMAD-CIS usage may mention these commands or personas:
bmad-cis-brainstormingbmad-cis-design-thinkingbmad-cis-innovation-strategybmad-cis-problem-solvingbmad-cis-storytellingTreat them as mode hints, not separate first-class workflows. Map them into the modern modes above:
problem framing or concept shapingaudience and value framing or concept shapingstory packagingAlways return a short operator-style idea routing brief.
Required qualities:
Input
Use bmad-idea. We think there is an opportunity around AI-assisted team handoffs, but we do not know the sharp problem or who it is really for.
Output sketch
problem framingproblem briefbmadInput
We built a workflow tool, but our messaging is fuzzy and every pitch sounds generic.
Output sketch
audience and value framingpositioning briefmarketing-automationInput
Help us shape a cozy automation game idea before we start a real GDD.
Output sketch
game concept framinggame concept packetbmad-gdsbmad, task-planning, marketing-automation, and bmad-gds each own later-stage work.../bmad/SKILL.md../task-planning/SKILL.md../marketing-automation/SKILL.md../bmad-gds/SKILL.md