# Concept Generator > Generate ranked native social carousel concepts, pick one, draft a script with frontmatter compliant with v0.7.0 formats. Produces concepts.md, concept-pick.md, script.md, and concept-meta.json for downstream styled-carousel rendering. Do NOT use for: image generation, post scheduling, or non-carousel content (X threads, X articles, newsletter). - Skill: `themattberman/concept-generator` (Agent Skill, multi-file: 5 files) - Install (CLI): `npx skillmds@latest add themattberman/concept-generator` - Raw SKILL.md: https://api.skillmd.com/api/skills/themattberman/concept-generator/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: TheMattBerman (https://skillmd.com/u/themattberman) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/themattberman/concept-generator --- # Concept Generator (DNA-Lens) Three-stage pipeline that replaces the host-agent-freestyle script-generation gap. Each stage runs as a separate script; chain them via the daily-loop workflow. ## Pipeline 1. **generate_concepts.sh** -> writes `runs//concepts.md` 2. **pick_concept.sh** -> writes `runs//concept-pick.md` 3. **draft_script.sh** -> writes `runs//script.md` + `concept-meta.json` ## Inputs - Brand workspace at `//` with at minimum a `brand-voice.md`. Richer corpora (voice-profile.md, deliverables/recent/) produce better output. - Trend research input from daily-loop Step 4 (markdown file with operator's hot takes on selected trends). ## Modes - `interactive` (default): Stage 3 elicits operator specifics before drafting any concept that claims a personal fact. Recommended for own-brand work. - `autopilot`: Stage 3 never elicits; concepts claiming personal facts are down-ranked at Stage 1 so the auto-picker avoids them. Recommended for agency / scaled work. Mode resolves from: `--mode` flag > brand `config.json` `concept_mode` field > default `interactive`. ## Stage 1: generate_concepts.sh Loads brand corpus via `lib.concept_corpus.load_brand_corpus`, reads the trend input, and prompts the host agent (via the `concept_generation` template in `prompts.json`) to produce N ranked concepts. Each concept has: - `format` (one of v0.7.0's seven formats) - `close_action` (save / share / comment / soft) - `arc` (1-line summary) - `why_this_works` (3-5 sentences) - `claims_personal_fact` (true if any concept-level fact requires operator confirmation in Stage 3) - 3-5 `hook_variants`, each with text, pattern (one of six in `references/hook-patterns.md`), and 360 shock-score - `concept_score` (aggregate 0-10) Output: `runs//concepts.md` with markdown sections per concept, ranked top-to-bottom by concept_score. In autopilot mode, concepts where `claims_personal_fact: true` get a -2 score penalty so the auto-picker avoids them. Operator still sees them. ## Stage 2: pick_concept.sh In interactive mode, the operator (or upstream agent) provides `--concept N` to pick the Nth ranked concept. In autopilot mode (no `--concept`), the script picks the highest-ranked autopilot-safe concept (claims_personal_fact false). If all concepts claim personal facts in autopilot, the script exits non-zero with a clear error. Output: `runs//concept-pick.md` (a copy of the picked concept's section + the chosen hook variant; first hook variant by default). ## Stage 3: draft_script.sh Reads `concept-pick.md`. In interactive mode, if the picked concept has `claims_personal_fact: true`, prompts the host agent to elicit specifics from the operator using the `scene_elicitation` template. The agent asks the minimum questions documented in that template ("Have you actually X?", "What's your real number / date / situation?"). Operator answers; agent collects. Then prompts the host agent (via `script_draft` template) to write the full script. Format slot template loaded from `lib.format_registry.get_format`; slide bodies match alias headings. Pre-output lint chain (any failure aborts): 1. `lib.voice_lint.lint_text` (v0.6.1): em-dash, AI-tell patterns, banned words. `--no-lint` bypasses. 2. `lib.format_lint.lint_script_structure` (v0.7.0): slot count, word count, close vocab. `--no-format-check` bypasses. Per-style `style.yaml` `word_count_override` (v0.8.0) applies when present (set `BRAND_STYLE_DIR` env var to point at the brand's style directory). 3. `lib.save_filter.check_save_worthiness` (v0.8.1): heuristic gate (numbers, dates, named frameworks, paired quotes, tactical asides) + optional LLM fallback. `--no-save-filter` bypasses. Adapts to effective word-cap: tight slots (max <=12) need >=1 marker; standard slots (>=13) need markers from >=2 categories. Output: `runs//script.md` (frontmatter + slot bodies) and `runs//concept-meta.json` (data foundation for v0.8.1+ ingestion loop). **Non-dry-run invocation contract:** the script expects `script.md` to already be present in `--run-dir` (the host agent writes it after reading the `script_draft` template + concept-pick.md). draft_script.sh then runs the 3-step lint chain and emits concept-meta.json. Bypass any step with `--no-lint`, `--no-format-check`, `--no-save-filter`. ## References (one level deep) - `references/hook-patterns.md`: six hook patterns with exemplars - `references/concept-patterns/`: kit-shipped concept exemplars (six files) - `references/carousel-examples/`: operator-supplied annotated carousel reference (empty in default install; ingested when Matt provides) - `references/formats/`: v0.7.0 format YAML files (consumed via `lib.format_registry`) ## Authoring a new hook pattern The six patterns are sufficient per Bug 12. To add a seventh: append an entry to `lib/hook_patterns.HOOK_PATTERNS` with description, exemplars, and when_to_use. Mirror in `references/hook-patterns.md`. Tests enforce sync. ## Authoring a new concept pattern Drop a markdown file in `references/concept-patterns/` matching the existing shape (Shape / Hook style / Format hint / Body density markers / Close style / Why it saves / Source exemplars). The skill loads all `*.md` files in the directory automatically.