This is a reference document, not an executable skill. It has two layers. The first is the format taxonomy — the full set of ad video formats available in the system, their production profiles, their Meta Andromeda Entity ID signals, and the visual characteristics that make each one distinct from the others. The second layer is scripting mechanics — the detailed section-by-section structure for the three non-standard format modes (Skillshow Notebook, 2-Person, and FAQ Phone Scroll). The ad-scripter-write skill loads this reference as context whenever a script is requested in a non-standard format. Format-Hermes reads the taxonomy layer when making format recommendations for a batch. The production-brief skill reads it to validate format slugs. Because it is a reference, it gets a currency check on each sweep — not golden-case evals.
The system's product requirements document (PRD) targets approximately 22 formats across video, static, carousel, and user-generated content families. The repository currently implements 14 video formats in style-system.md (the taxonomy source) and 3 scripting modes in format-reference.md. Static, carousel, and formats such as podtalk and skit do not yet have repository specifications. This dossier documents what exists today. The delta to ~22 is flagged as a build gap for operator review.
This file does not run a model. It is loaded as context by the skills that do.
| Consumer | What it reads | How it uses it |
|---|---|---|
| Format-Hermes (in-batch function) | The 14 format profiles — EC Prior (Entity Capture Prior) values, Entity ID signal taxonomy, format × arc matching table, Entity ID separation matrix | Generates format mix recommendations for a batch. Selects formats that spread the batch across at least 4–5 distinct Andromeda entity classes. Emits recommended_formats[] on the Construct Brief that ad-ideate then weights by. |
| ad-scripter-write (operator command) | The scripting mechanics section — section-by-section structure for SKILLSHOW_NOTEBOOK, 2-PERSON-FRIENDS, 2-PERSON-RECOGNITION, FAQ_PHONE_SCROLL | When Format Mode on the concept card is not SOLO, the scripter loads the relevant mechanics block and produces a format-compliant script (correct section count, word count, stage direction conventions, proof placement rules). |
| ad-ideate | Format profiles — EC Prior, arc fit, pathway availability from production-pathways.md | Selects format for each concept card from the Format-Hermes recommended mix, filtered by non-BLOCKED pathways. |
| ad-ideate | Pathway status per format | Rejects any concept whose format is BLOCKED across all production pathways. Flags IN-TEST pathways with a validation caveat. |
| ad-production-brief | rc-ai-ugc slugs and format profile metadata | Validates the format slug from the concept card before generating the filming brief or AI user-generated content handoff package. |
Deterministic-first note: Format selection logic — counting formats per entity class, checking pathway availability, flagging blocked formats — is plain code. No model runs those checks. The model only reasons over the format profiles when synthesising a format recommendation narrative.
The 14 formats in the system today, how they are built, and why format diversity matters.
Meta's Andromeda algorithm assigns each creative an Entity ID based on visual signals it reads from the ad — environment, camera geometry, subject count, and format mechanics. Two ads with different Entity IDs compete for different audience sub-segments and scale independently without cannibalising each other. Running ten scripts in the same visual format gives the algorithm ten ads that look structurally identical, regardless of the words. Entity ID separation falls, fatigue windows compress, and the ceiling on reach shrinks. Format diversity is not a stylistic preference — it is the mechanism by which a winning message multiplies across new Entity IDs before it fatigues in the current one.
The 14 formats group into four entity-class families based on the primary Andromeda signal they generate:
| Family | Primary signal | Formats |
|---|---|---|
| Solo DTC (direct to camera) — talking head | Subject, camera geometry, environment | Selfie White Wall · Outdoor Walking Selfie · Seated Interior · Mirror Selfie · Street Interview · Park Bench |
| 2-Person | Subject count (1→2 is a primary Andromeda signal) | Pub Chat (Friends) · Stage Interview |
| Format-mechanic formats | Structural visual mechanic — text overlays, overhead angle, split-screen | FAQ Phone Scroll · Skillshow Notebook · This-or-That · Green Screen |
| Multi-scene / lifestyle | Multiple environment cuts within one ad | Multi-Scene Founder · Day in the Life |
Static, carousel, and formats such as podtalk, skit, and this-or-that (static variant) are PRD targets not yet specified in the repository. See the warning callout at the top of this dossier.
selfie-white-wall · Scripting mode: SOLO| Field | Value |
|---|---|
| Production method | Phone-held selfie, face forward, clean indoor background — white wall or minimal décor. |
| Entity ID signals | Face-forward, single subject, minimal environment detail, static or slight movement. |
| EC Prior vs baseline | LOW — the most common format in the avatar-match universe. Strong baseline for a first batch; low differentiation for iteration rounds. |
| Best arcs | Any arc — this is the universal fallback. Never more than 3 scripts in this format per batch. |
| Pathways | AI-UGC (IN-TEST) · INTERNAL-TEAM (VALIDATED) · EXTERNAL-ACTOR (VALIDATED) |
outdoor-walking-selfie · Scripting mode: SOLO| Field | Value |
|---|---|
| Production method | Phone-held selfie while walking outdoors. Dynamic environment, ambient light, changing background. |
| Entity ID signals | Outdoor environment, movement (camera and subject), ambient audio, changing background. |
| EC Prior vs selfie-white-wall | MEDIUM — outdoor + movement = two-dimension separation from white wall. Different entity class. |
| Best arcs | Direct Callout, income/lifestyle angles, energy-forward hooks. |
| Pathways | AI-UGC (IN-TEST) · INTERNAL-TEAM (VALIDATED) · EXTERNAL-ACTOR (VALIDATED) |
seated-interior · Scripting mode: SOLO| Field | Value |
|---|---|
| Production method | Subject seated indoors — desk, home office, studio, sofa. Face to camera. Static or minimal movement. |
| Entity ID signals | Specific interior environment (contextual props, décor), seated posture, controlled lighting. |
| EC Prior vs selfie-white-wall | MEDIUM — interior context adds environment signals. Desk/office signals authority differently from a white wall. |
| Best arcs | Authority/credentials angles, Gatekeeping Reveal arc, longer-form explanations. |
| Pathways | AI-UGC (IN-TEST) · INTERNAL-TEAM (VALIDATED) · EXTERNAL-ACTOR (VALIDATED) |
mirror-selfie · Scripting mode: SOLO| Field | Value |
|---|---|
| Production method | Subject filming their reflection. Phone visible in-frame. Bathroom, dressing room, or gym context. |
| Entity ID signals | Mirror reflection (subject appears at angle), phone in frame, specific room type. |
| EC Prior vs selfie-white-wall | MEDIUM-HIGH — reflection mechanic creates unique visual composition. Phone-in-frame is a structural feature Andromeda likely classifies distinctly. |
| Best arcs | Personal transformation angles, identity callout hooks, health and body verticals. |
| Pathways | AI-UGC (IN-TEST) · INTERNAL-TEAM (VALIDATED) · EXTERNAL-ACTOR (VALIDATED) |
street-interview · Scripting mode: SOLO| Field | Value |
|---|---|
| Production method | Subject on a busy street or urban environment. Blurred pedestrians, traffic, ambient noise behind them. |
| Entity ID signals | Outdoor urban environment, environmental depth (blurred movement behind subject), ambient sound texture. |
| EC Prior vs white wall | HIGH — outdoor urban creates clear multi-dimension separation: environment + ambient movement + lighting conditions. |
| Best arcs | Social proof delivery, income-first hooks, testimonial-style narration. Creates "overheard on the street" authenticity. |
| Pathways | AI-UGC (IN-TEST) · INTERNAL-TEAM (UNTESTED) · EXTERNAL-ACTOR (BLOCKED — public filming complications) |
park-bench · Scripting mode: SOLO| Field | Value |
|---|---|
| Production method | Subject seated on a park bench or natural outdoor setting. Natural light. Relaxed posture. |
| Entity ID signals | Natural outdoor environment, seated posture (different from walking), specific bench/nature context. |
| EC Prior vs street-interview | MEDIUM — shares outdoor environment but seated posture and natural vs urban context create moderate additional separation. |
| Best arcs | Conversational/confessional angles, Overwhelm-to-System arc with a calm resolution register. |
| Pathways | AI-UGC (IN-TEST) · INTERNAL-TEAM (VALIDATED) · EXTERNAL-ACTOR (VALIDATED) |
pub-chat · Scripting mode: 2-PERSON-FRIENDS| Field | Value |
|---|---|
| Production method | Two subjects in a social venue (pub, bar, restaurant). Conversational framing. Expert and interviewer/friend. |
| Entity ID signals | Two subjects (a primary Andromeda signal), social environment, conversational camera framing (wider to show both), ambient venue context. |
| EC Prior vs all solo formats | VERY HIGH — subject count shift from 1 to 2 is a primary Andromeda signal. Every 2-person format generates a fundamentally different entity class from solo formats. |
| Best arcs | Transformation narratives told as conversation. Interviewer reactions create emotional proof without explicit testimonials. |
| Pathways | AI-UGC (IN-TEST) · INTERNAL-TEAM (BLOCKED) · EXTERNAL-ACTOR (BLOCKED) — AI user-generated content locked in; live filming shelved pending operator approval. |
| Scripting mechanics | See format-reference.md 2-PERSON section: 7-section formula adapted to dialogue, interviewer voice rules (25–35 words total), CTA trigger mechanics (interviewer triggers the sell, never the expert). |
stage-interview · Scripting mode: 2-PERSON-RECOGNITION| Field | Value |
|---|---|
| Production method | Two subjects in a professional or event context. Microphones, event backdrop, slightly formal framing. |
| Entity ID signals | Two subjects, formal/professional environment, microphone props, event backdrop texture. |
| EC Prior vs pub-chat | MEDIUM — shares 2-person signal; formal environment adds separation from social-venue framing. |
| Best arcs | Credibility/authority angles, expert-as-guest positioning. |
| Pathways | AI-UGC (IN-TEST) · INTERNAL-TEAM (UNTESTED) · EXTERNAL-ACTOR (BLOCKED — live filming needs a real event) |
skillshow · Scripting mode: SKILLSHOW_NOTEBOOK| Field | Value |
|---|---|
| Production method | Overhead camera. Subject's hands and an iPad on a flat surface. Subject swipes through slides. Face-to-camera for hook and call-to-action bookends only. |
| Entity ID signals | Overhead camera angle (unique in the format set), hands-and-device visual, progressive reveal mechanic (slides one by one), no or minimal face. |
| EC Prior vs all talking-head formats | VERY HIGH — camera geometry is the strongest single signal. Overhead is visually unlike every other format. Guaranteed Entity ID separation from any talking-head variant. |
| Best arcs | Mechanism/credentials angles, Overwhelm-to-System arc with visual teaching structure. |
| Pathways | AI-UGC (BLOCKED — not viable) · INTERNAL-TEAM (IN-TEST) · EXTERNAL-ACTOR (IN-TEST) |
| Scripting mechanics | 6 sections (not 7), 90–120 seconds, 250–350 words. First swipe within 5 seconds. Proof woven into teaching steps, not held for a separate Social Proof Bridge. Step 6B: Nano Banana Pro (NBP Pro) slideshow prompts generated after operator approves the script. |
faq-phone-scroll · Scripting mode: FAQ_PHONE_SCROLL| Field | Value |
|---|---|
| Production method | Subject face-to-camera (selfie or seated). Text overlay questions appear on screen in post-production. Expert answers conversationally, as if responding to a comment or DM. |
| Entity ID signals | Text overlay mechanics (structural visual element on top of talking head), question-answer pacing creates a visual rhythm distinct from continuous narration. |
| EC Prior vs selfie-white-wall | MEDIUM — text overlays add a structural visual layer Andromeda likely classifies distinctly. Same face-forward geometry limits separation. |
| Best arcs | Objection-handling angles, warm retargeting, high-volume rapid-fire content. Best for Solution-Aware or Product-Aware traffic. |
| Pathways | AI-UGC (IN-TEST) · INTERNAL-TEAM (VALIDATED) · EXTERNAL-ACTOR (VALIDATED) |
| Scripting mechanics | 5–6 sections (1 hook question + 3–4 Q&A pairs + call to action), 45–90 seconds, ~150–220 words. Expert never reads the question aloud. Each answer 15–40 words. At least 2 answers include a proof element. Expert introduces themselves in Q2, not before. |
green-screen · Scripting mode: SOLO| Field | Value |
|---|---|
| Production method | Subject in front of a digital background replaced via chroma key. Background can be any image, graphic, or video. |
| Entity ID signals | Background type (digital/graphic vs real environment), potential for on-screen data visualisations or supporting graphics behind subject. |
| EC Prior | MEDIUM — depends heavily on background content. Plain colour = low separation; chart or dramatic visual = higher separation. |
| Best arcs | Data-heavy angles, contrarian/myth-bust hooks with on-screen supporting visuals. |
| Pathways | AI-UGC (IN-TEST) · INTERNAL-TEAM (BLOCKED — requires physical green screen rig) · EXTERNAL-ACTOR (UNTESTED) |
multi-scene-founder · Scripting mode: SOLO| Field | Value |
|---|---|
| Production method | Multiple cuts across different locations or contexts. Documentary-style. Voiceover drives the narrative while B-roll or multiple scenes play. |
| Entity ID signals | Multiple visual contexts (cuts between environments), voiceover-driven structure, documentary pacing. |
| EC Prior | HIGH — multi-scene creates multiple environment signals within one ad. Andromeda reads scene transitions as structural complexity distinct from any single-scene format. |
| Best arcs | Origin story arcs, Gatekeeping Reveal, longer transformation narratives. |
| Pathways | AI-UGC (IN-TEST) · INTERNAL-TEAM (BLOCKED) · EXTERNAL-ACTOR (BLOCKED) — AI user-generated content via multi-clip stitch with consistent identity anchor. |
day-in-the-life · Scripting mode: SOLO| Field | Value |
|---|---|
| Production method | Multiple brief clips across different times and contexts within a single day. Aspirational lifestyle framing. |
| Entity ID signals | Time-of-day variation (morning/afternoon/evening), lifestyle location variety (home, coffee shop, workout, work), aspirational aesthetic. |
| EC Prior | HIGH — lifestyle variety across scenes creates multi-environment signals. Lighter narration and stronger lifestyle/aspiration register than Multi-Scene Founder. |
| Best arcs | Income-First Curiosity arc, lifestyle-as-proof angles, aspirational identity hooks. Most effective for Unaware to Problem-Aware traffic. |
| Pathways | AI-UGC (IN-TEST) · INTERNAL-TEAM (BLOCKED) · EXTERNAL-ACTOR (BLOCKED) — previously shelved; AI user-generated content makes viable via multi-clip. |
this-or-that · Scripting mode: SOLO| Field | Value |
|---|---|
| Production method | Split-screen or rapid alternation between two contrasting options, scenes, or states. Visual binary comparison. |
| Entity ID signals | Split-screen or rapid-cut mechanics, visual binary structure, comparison framing. |
| EC Prior | MEDIUM-HIGH — split-screen or rapid alternation is a distinct structural mechanic. |
| Best arcs | Negative Elimination arc ("not this, not that — but this"), myth-bust hooks, before/after framing. |
| Pathways | AI-UGC (IN-TEST) · INTERNAL-TEAM (IN-TEST) · EXTERNAL-ACTOR (UNTESTED) |
The rule for ideation: a concept may emit a format if at least one pathway column is not BLOCKED. Dual-pathway formats defer routing to scripting-approval time.
| Format | AI-UGC | Internal Team | External Actor |
|---|---|---|---|
| Selfie White Wall | IN-TEST | VALIDATED | VALIDATED |
| Outdoor Walking Selfie | IN-TEST | VALIDATED | VALIDATED |
| Seated Interior | IN-TEST | VALIDATED | VALIDATED |
| Mirror Selfie | IN-TEST | VALIDATED | VALIDATED |
| Street Interview | IN-TEST | UNTESTED | BLOCKED |
| Park Bench | IN-TEST | VALIDATED | VALIDATED |
| Pub Chat (2-Person Friends) | IN-TEST | BLOCKED | BLOCKED |
| Stage Interview | IN-TEST | UNTESTED | BLOCKED |
| Skillshow Notebook | BLOCKED | IN-TEST | IN-TEST |
| FAQ Phone Scroll | IN-TEST | VALIDATED | VALIDATED |
| Green Screen | IN-TEST | BLOCKED | UNTESTED |
| Multi-Scene Founder | IN-TEST | BLOCKED | BLOCKED |
| Day in the Life | IN-TEST | BLOCKED | BLOCKED |
| This-or-That | IN-TEST | IN-TEST | UNTESTED |
Use format combinations with HIGH or VERY HIGH separation to maximise Andromeda entity diversity across a batch. A pioneer batch of 10 scripts should aim for at least 4–5 distinct entity classes.
| Format A | Format B | Separation | Reason |
|---|---|---|---|
| Any solo DTC | Any 2-person format | VERY HIGH | Subject count shift (1→2) is a primary Andromeda signal. |
| Any solo DTC | Skillshow Notebook | VERY HIGH | Camera geometry (overhead vs face-forward) — the strongest single dimension. |
| Selfie White Wall | Street Interview | HIGH | Indoor minimal vs outdoor urban with ambient movement. |
| Outdoor Walking Selfie | Seated Interior | MEDIUM | Movement + outdoor vs static + interior — two dimensions but both solo. |
| Selfie White Wall | FAQ Phone Scroll | MEDIUM | Text overlay mechanic adds a structural layer, but face-forward geometry is shared. |
| Selfie White Wall | Outdoor Walking Selfie | LOW–MEDIUM | Only one dimension of difference (indoor vs outdoor). Too similar for entity separation at scale. |
Three representative profiles showing how a format card looks when Format-Hermes emits it to the Construct Brief.
--- FORMAT PROFILE: Selfie White Wall --- slug: selfie-white-wall scripting_mode: SOLO family: Solo DTC (direct to camera) ec_prior: LOW entity_class: 1 (face-forward, single subject, minimal environment) entity_id_signals: - Face-forward, single subject - Minimal environment detail (white or near-white background) - Static or slight movement pathway_availability: ai_ugc: IN-TEST internal_team: VALIDATED external_actor: VALIDATED best_arcs: - Any arc — this is the universal fallback - Direct Callout (strongest match) batch_cap: 3 (never more than 3 in a batch of 10) scripting_notes: > Standard SOLO 7-section formula applies. No format-specific mechanics. Load ad-scripter-reference for word counts and section targets. --- FORMAT PROFILE: Pub Chat (2-Person Friends) --- slug: pub-chat scripting_mode: 2-PERSON-FRIENDS family: 2-Person ec_prior: VERY HIGH entity_class: 4 (2-person, social environment) entity_id_signals: - Two subjects in frame (primary Andromeda signal) - Social venue environment (pub, bar, restaurant) - Conversational camera framing (wider than solo) - Ambient venue context pathway_availability: ai_ugc: IN-TEST # CURRENT primary path — AI-UGC locked in internal_team: BLOCKED # Live filming shelved pending operator review external_actor: BLOCKED best_arcs: - Transformation narratives told as conversation - Social proof via interviewer reactions (implicit, not stated) scripting_notes: > Load format-reference.md — 2-PERSON-FRIENDS section. 7-section formula adapted to dialogue. Interviewer word count: 25–35 total. CTA trigger: interviewer references their person (girlfriend, mum, friend) — expert never initiates the sell. Location options: cafe, pub, park bench, restaurant — same script serves 2–3 locations, note in brief. --- FORMAT PROFILE: FAQ Phone Scroll --- slug: faq-phone-scroll scripting_mode: FAQ_PHONE_SCROLL family: Format-mechanic ec_prior: MEDIUM entity_class: 3 (text overlay, Q&A structure) entity_id_signals: - Text overlay questions (structural visual element) - Q&A pacing rhythm (distinct from continuous narration) - Face-forward geometry (shared with solo DTC — limits separation) pathway_availability: ai_ugc: IN-TEST internal_team: VALIDATED external_actor: VALIDATED best_arcs: - Objection-handling (Solution-Aware or Product-Aware traffic) - Warm retargeting scripting_notes: > Load format-reference.md — FAQ_PHONE_SCROLL section. Structure: 1 hook question + 3–4 Q&A pairs + CTA. Duration: 45–90 seconds, ~150–220 words. Expert NEVER reads the question aloud — text overlay only. Each answer: 15–40 words. At least 2 answers include a proof element (pioneer name + concrete outcome). Expert introduces themselves in Q2, not before Q1. Q1 IS the hook.
| Term | In full / what it means |
|---|---|
| DTC | Direct to Camera — A video style where the presenter speaks directly into the camera lens, creating a one-on-one feel. The dominant style for most formats in this system. Abbreviated DTC throughout the creative system; always spelled out here and on first use in any human-facing document. |
| UGC | User-Generated Content — An ad style that mimics organic, creator-style content — informal, handheld, less polished. In this system, AI user-generated content refers to creatives produced via the ugc-factory pipeline (Nano Banana Pro → Enhancor → Seedance 2.0) rather than filmed by a real person. |
| AI-UGC | AI User-Generated Content (production pathway) — The production route that uses the ugc-factory extension (Nano Banana Pro identity lock → Enhancor → Seedance 2.0) to generate video without a real actor. One of three production pathways alongside INTERNAL-TEAM (Bonnie or internal operator films) and EXTERNAL-ACTOR (contracted actor films). |
| Entity ID | Andromeda Entity ID — A unique identifier Meta's Andromeda algorithm assigns to each creative based on the visual signals it reads from the ad. Two creatives with the same Entity ID compete for the same audience sub-segment. Two creatives with different Entity IDs compete independently and can scale without cannibalising each other. Format diversity is the primary mechanism for generating distinct Entity IDs. |
| Andromeda | Andromeda (Meta's ad delivery algorithm) — Meta's system for deciding which creative to show to which person. It reads visual signals from the ad — environment, camera geometry, subject count, format mechanics — and uses them to assign Entity IDs and route ads to audience sub-segments. Understanding Andromeda's signal taxonomy is the reason this format taxonomy exists. |
| EC Prior | Entity Capture Prior — A first-principles estimate of how much Andromeda Entity ID separation a given format produces relative to what is already in the footage library. Scored per format in style-system.md. Values are currently theoretical, not measured. Used by ad-creative-strategy to score iteration paths. Format combinations rated HIGH or VERY HIGH are prioritised in batch planning. |
| Format families | Format families (entity class groupings) — The four groupings in this system: Solo DTC (direct to camera) talking head (Selfie White Wall, Outdoor Walking, Seated Interior, Mirror Selfie, Street Interview, Park Bench); 2-Person (Pub Chat, Stage Interview); Format-mechanic formats (FAQ Phone Scroll, Skillshow Notebook, This-or-That, Green Screen); Multi-scene/lifestyle (Multi-Scene Founder, Day in the Life). |
| rc-ai-ugc slug | rc-ai-ugc slug (format identifier string) — The lowercase-hyphenated identifier used to refer to a format in production pipeline files, motion profile JSON files, and the production-brief skill. Example: faq-phone-scroll. Distinct from Format Mode names (all-caps, underscore-separated) used in ad-scripter-write — the relationship is many-to-one: one scripting Format Mode (e.g. 2-PERSON-FRIENDS) can be filmed across multiple rc-ai-ugc slugs (e.g. pub-chat, park-bench). |
| Format Mode | Format Mode (scripting mode identifier) — The all-caps, underscore-separated label used in ad-scripter-write to select which scripting structure to apply. Five modes: SOLO (standard 7-section formula), SKILLSHOW_NOTEBOOK, 2-PERSON-FRIENDS, 2-PERSON-RECOGNITION, FAQ_PHONE_SCROLL. One mode can map to multiple rc-ai-ugc slugs. |
| SOLO | SOLO (scripting mode) — The default scripting mode. One expert, speaking directly to camera, 7-section formula, 190–250 words. Applies to Selfie White Wall, Outdoor Walking Selfie, Seated Interior, Mirror Selfie, Street Interview, Park Bench, Green Screen, Multi-Scene Founder, Day in the Life, and This-or-That. |
| Podtalk | Podtalk (PRD target format — not yet in repo) — A podcast-style format where the expert sits at a desk or table with a visible microphone, as if being recorded for a podcast or interview show. The closest repo analog is Stage Interview. Podtalk is named in the system PRD (product requirements document) as part of the ~22-format target set but has no rc-ai-ugc slug, scripting mechanics, or pathway specification in the current repository. |
| Voice Book | Voice Book (Layer 2 expert data) — The structured expert voice artifact built by ad-voice-profile. Contains signature language patterns, tone fingerprints, forbidden words, and proof delivery style for a specific expert. Ad-scripter-write loads the Voice Book at every invocation and halts if it is empty for the named expert. Previously called "Layer 3 calibration" — that name is deprecated; do not use it. |
| NBP Pro | Nano Banana Pro — The image generation tool used to produce individual slide images for Skillshow Notebook format. Prompts are generated in Step 6B of the Skillshow scripting process, after the operator approves the script. Slides are loaded onto an iPad as a swipeable slideshow. |
| CPBC | Cost Per Booked Call — How much money was spent on Meta ads to get one person to book a sales call with the expert. The primary success metric for top-of-funnel (TOF) cold traffic. Target threshold per expert lives in expert_config.target_cpbc in Supabase. |
| TOF | Top of Funnel — Cold traffic — people who have never seen the expert's content before. Most of this system's formats are designed for top-of-funnel audiences. Middle of funnel (MOF) warm retargeting uses a different format and hook mix. |
| Social Proof Bridge | Social Proof Bridge (non-negotiable script element) — The section in the standard 7-section ad formula where proof entries (pioneer name + concrete outcome) are delivered. Non-negotiable in all SOLO format scripts. In Skillshow Notebook, proof is woven into teaching steps rather than held for a separate bridge section. |
| Pioneer mode | Pioneer mode (operating mode) — The operating mode for first-batch creative work against a new expert or new market position, where no own-performance data exists. Format selection in Pioneer mode relies on competitor intelligence and theoretical EC Prior values. |
| Iteration mode | Iteration mode (operating mode) — The operating mode for subsequent batches, where live performance data from Fibery/Supabase is available. Format selection weights toward formats that have demonstrated EC Prior separation in practice, validated by the creative-strategy skill's path scoring. |
| Fibery | Fibery (project management and system of record) — The system of record for all creative entities, production status, and Meta performance data. Downstream of scripting — ad-log writes to Fibery; scripting skills read from Supabase views, never Fibery directly at runtime. |
| Supabase | Supabase (database platform) — The PostgreSQL-based database hosting the SKL ad creative system data layer — all seven layers from raw ad captures through to launch learnings. Scripting skills read from Supabase views (expert config, proof bank, Voice Book). |
| OpenRouter | OpenRouter (model routing proxy) — The API gateway through which all language model calls in this system are routed. Provides unified billing, model switching, and per-call logs (model identifier, provider, cost) that feed the agent_run audit trail. |