# Creative Finder (ListeningMind)

> Give one to three product lines. The app finds the moments when people think of them in ListeningMind DaaS data (related searches, real search paths, monthly volume), grades the evidence in code, and writes a 15-second creative draft with a distinct tone per moment. Images and 8-second vertical videos can be generated per draft. Markets KR, JP, US; UI ko, en, ja.

Korean: 검색 데이터에서 구매 상황(CEP)을 찾아 상황별 광고 소재안과 이미지·영상 시안을 만듭니다 · Japanese: 検索データから購買状況（CEP）を見つけ、状況ごとの広告素材案と画像・動画案をつくります

## Use it as an agent
- [MCP server](https://daas-creative.listeningmind.ai/mcp): Streamable HTTP, JSON-RPC. 16 app tools plus app_guide, result store tools (results_sync, results_list, results_get, results_compare, results_export) and settings sweeps (plan_batch, batch_status)
- WebMCP: every page of this app registers the same tools in `document.modelContext` for a browser agent; calls that spend credits ask the person on the page
- [OpenAPI](https://daas-creative.listeningmind.ai/.well-known/openapi.json): the same tools as a REST contract (operationId = tool name)
- [agents.md](https://daas-creative.listeningmind.ai/agents.md): step-by-step guide · [API catalog](https://daas-creative.listeningmind.ai/.well-known/api-catalog) · [MCP server card](https://daas-creative.listeningmind.ai/.well-known/mcp/server-card.json)
- Every page answers `Accept: text/markdown` with a markdown version
- Tools of kind run or delete spend credits or delete data: over MCP the call returns confirm_url for a person, then call confirmation_status
- Accounts: reading results and history is open. Starting a run or changing data needs a ListeningMind member: the person approving confirm_url signs in or [signs up](https://daas-creative.listeningmind.ai/_lm/auth/signup); other changes over MCP need the member's agent key (LM-User-Key header, created at https://daas-creative.listeningmind.ai/_lm/account)

## What you give and what you get
- Inputs: lines (1-3 product line keywords with search volume), gl (kr|jp|us), lang (ko|en|ja), depth (quick|standard|deep), audience, channel, reg_domain, principles[], exclude_topics[], fixed_elements, creatives_per_line (3-6). Brief assistant: one keyword.
- Outputs: lines, market (growing, declining, new), ceps (situations with trigger type, basket keywords and volume, evidence grade, consumer question), matrix, unobserved_paths, big_outside, creatives (scene, lines, 4 shots, format, test question, KPI, review notes, tone, image and video prompts), notes, credits. Exports: report.html, brief.md, run.json. Generated assets: image and video files.
- Cost: standard about 35,000-45,000 credits (7 path_finder calls), quick about 1,000-3,000, deep about 70,000. Brief assistant about 500. One image about 40-130 credits, one 8-second video about 400-1,200 credits (1 USD = 1,000 credits).

## How a result is made (in order)
1. `assist_brief`: Fill product lines, regulatory domain and principles from one keyword
2. `check_keywords`: Check volume of hand-typed lines
3. `estimate_run`: Estimate credits before the run
4. `start_run`: Start the run
5. `get_run_status`: Poll until done
6. `get_run`: Read the result
7. `generate_image`: Image draft for a creative
8. `generate_video`: Video draft for a creative
9. `list_assets`: Check generated assets
10. `get_report_html`: Export the report

Run stages reported by the app: market → seeds → paths → situations → evidence → relations → creatives → done

## Method (how the analysis works)
1. Read the market from the product lines' volume and related searches (growing, falling, new queries).
2. Find the purchase situations in real search paths (path_finder).
3. Code grades each situation's evidence (path confirmed, related confirmed, hypothesis) and adds basket query volume.
4. Write a 15-second draft per situation with its own tone, a wording check, and image and video prompts.

## Reading the result
- ceps lists the purchase situations; evidence is the grade. Read hypothesis-grade ones with their test questions.
- creatives holds one draft per situation, with a softer variant and a wording check; all are pre-review drafts.
- credits.spent is what the run used; own_cache is what your own cache saved.

## Requests this app answers well
- Find the purchase situations for probiotics and draft a Reels ad for each
- Draft 15-second ads and images for each buying situation of sunscreen in Japan
- Soften this draft's wording for health supplement ad review
- Make vertical video drafts only for situations confirmed by search paths

## Continue in another app
- [CEP Finder](https://daas-cep.listeningmind.ai/llms.txt) (MCP `https://daas-cep.listeningmind.ai/mcp`): When you need the full map and priority of a category's entry points. Carry: The same product line keyword and market.
- [Demand Forecast](https://daas-forecast.listeningmind.ai/llms.txt) (MCP `https://daas-forecast.listeningmind.ai/mcp`): When you want to know when to run the ads and when each situation's demand rises. Carry: The basket queries of confirmed situations (up to 5) as seeds.

## Using the screens (browser agents)
- `describe_screen`: menus, tabs, fields and buttons of the current screen, and what the page is for
- `go_to`: open a menu or page of this app by its label or path
- `fill_field`: type a value into a field by its label (never presses run; runs go through the run tools, which ask the person)
- `read_this_page`: the text and ids of what the person is looking at

## Tools
- `assist_brief` (run, POST /api/assist/brief): Measures one keyword, pulls its related searches and proposes product lines (with volume), regulatory domain, audience, channel, principles and fixed elements. Returns credits spent. About 500 Data API credits, 10-20 seconds.
- `check_keywords` (run, POST /api/assist/keywords): Returns monthly search volume for up to 3 hand-typed product line keywords. 1 credit per keyword.
- `estimate_run` (read, POST /api/estimate): Estimated credits for a run with these lines and depth, plus Lima. Free.
- `start_run` (run, POST /api/runs): Starts the full pipeline in the background and returns run_id and estimate_credits. standard depth takes 5-10 minutes and about 35,000-45,000 Data API credits plus a small LLM cost.
- `get_run_status` (read, GET /api/runs/{run_id}/status): Status, stage, percent and credits spent so far. Repeat until status is done or error.
- `get_run` (read, GET /api/runs/{run_id}): Full result JSON of a finished run (lines, market, ceps, matrix, creatives, notes, credits) plus generated assets.
- `list_runs` (read, GET /api/runs): Runs of the signed-in member (all runs for staff), newest first.
- `regenerate_creative` (run, POST /api/runs/{run_id}/creatives/{creative_id}/regenerate): Rewrites one creative draft with the person's instructions (new tone allowed). Small LLM cost, reported in credits.
- `generate_image` (run, POST /api/runs/{run_id}/creatives/{creative_id}/image): Starts image generation for one creative in the background (Gemini image or OpenAI image). Returns the asset row; poll list_assets until status is done. About 40-130 credits per image.
- `generate_video` (run, POST /api/runs/{run_id}/creatives/{creative_id}/video): Starts an 8-second vertical video for one creative (Veo 3.1 fast/lite or Sora 2). Poll list_assets until done. About 400-1,200 credits per clip.
- `generate_media_batch` (run, POST /api/runs/{run_id}/media/batch): Starts images or videos for every creative that has none yet. Returns started asset ids and the estimate.
- `list_assets` (read, GET /api/runs/{run_id}/assets): All generated images and videos of a run with status, file name and credits. Files are served at /api/runs/{run_id}/assets/{file}.
- `get_report_html` (read, GET /api/runs/{run_id}/report.html): Standalone HTML report of a finished run (sections A to F and appendix). embed=1 inlines generated images.
- `get_brief_md` (read, GET /api/runs/{run_id}/brief.md): Markdown brief of a finished run.
- `get_run_json` (read, GET /api/runs/{run_id}/run.json): Downloadable JSON of the result and assets.
- `delete_run` (delete, DELETE /api/runs/{run_id}): Deletes a run and its asset rows (owner or staff only).

## Pages
- [New run](https://daas-creative.listeningmind.ai/): Fill the brief from one product name and start a run
- [Results](https://daas-creative.listeningmind.ai/runs): Your runs
- [Method](https://daas-creative.listeningmind.ai/method): Steps, evidence grades, cost, limits

## Limits
- Markets KR, JP, US. Lines need search volume. One path_finder call is about 4,600 credits. Every draft is pre-review and does not replace advertising review in regulated domains. Images never contain text.

## The ListeningMind apps (same account, same tools, call any of them)
Each app has `/mcp`, `/llms.txt`, `/agents.md` and WebMCP on its pages. `family_apps` and `recommend_app` return this list with addresses.
- [ACO](https://daas-aco.listeningmind.ai/llms.txt): Diagnoses whether a product detail page can be cited by AI answers and used by shopping agents (MCP `https://daas-aco.listeningmind.ai/mcp`)
- [AOO](https://daas-aoo.listeningmind.ai/llms.txt): Measures whether AI agents can get real tasks done on a website (MCP `https://daas-aoo.listeningmind.ai/mcp`)
- [Brand Finder](https://daas-brand.listeningmind.ai/llms.txt): Which brands lead search by generation or field, and what their brand assets are (MCP `https://daas-brand.listeningmind.ai/mcp`)
- [Brand Naming Agent](https://daas-naming.listeningmind.ai/llms.txt): Creates and checks brand name candidates grounded in search data (MCP `https://daas-naming.listeningmind.ai/mcp`)
- [Brand Wiki](https://daas-wiki.listeningmind.ai/llms.txt): Turns a brand website into the entities, wiki pages and evidence AI assistants read (MCP `https://daas-wiki.listeningmind.ai/mcp`)
- [CEP Finder](https://daas-cep.listeningmind.ai/llms.txt): In which situations do people start looking for this category (category entry point map) (MCP `https://daas-cep.listeningmind.ai/mcp`)
- [Demand Forecast](https://daas-forecast.listeningmind.ai/llms.txt): What category demand looks like in the next 3-6 months and when to launch or campaign (MCP `https://daas-forecast.listeningmind.ai/mcp`)
- [Funnel Leak Finder](https://daas-funnel.listeningmind.ai/llms.txt): Where category search journeys leak to competitors (MCP `https://daas-funnel.listeningmind.ai/mcp`)
- [GEO Audit](https://daas-geo.listeningmind.ai/llms.txt): Checks whether a web page is ready to be read and cited by search engines and AI answer engines (MCP `https://daas-geo.listeningmind.ai/mcp`)
- [ICSS](https://daas-icss.listeningmind.ai/llms.txt): Synthetic consumer panel conditioned on search intent, for surveys and FGDs (MCP `https://daas-icss.listeningmind.ai/mcp`)
- [Intent KG](https://daas-intent.listeningmind.ai/llms.txt): What people look for about a topic, why, and how they choose (Intent Knowledge Graph) (MCP `https://daas-intent.listeningmind.ai/mcp`)
- [Prompt Builder](https://daas-prompt.listeningmind.ai/llms.txt): Finds what consumers ask AI and builds managed brand prompts with AI visibility (MCP `https://daas-prompt.listeningmind.ai/mcp`)
- [Pulse Finder](https://daas-pulse.listeningmind.ai/llms.txt): What is rising in search for a gender and age segment right now (MCP `https://daas-pulse.listeningmind.ai/mcp`)
- [Smart Store Suite](https://daas-store.listeningmind.ai/llms.txt): Which Smart Store products to grow, and how to rewrite their titles and detail pages in searchers' words (MCP `https://daas-store.listeningmind.ai/mcp`)
- [Taste Finder](https://daas-taste.listeningmind.ai/llms.txt): In what sensory and emotional words do people choose this (consumer taste report from search data) (MCP `https://daas-taste.listeningmind.ai/mcp`)
- [ListeningMind Data API](https://daas.listeningmind.ai/llms.txt): the search data behind every app (MCP `https://daas.listeningmind.ai/mcp`) · [glossary](https://daas.listeningmind.ai/en/glossary) · [all apps](https://daas.listeningmind.ai/en/apps)

## Optional
- ListeningMind data and other apps: https://www.listeningmind.com · contact m-support@listeningmind.com