# Pulse Finder (ListeningMind)

> ListeningMind Audience Pulse. It harvests candidate keywords from seed keywords or categories, measures gender and age share, 48-month search volume and SERP / AI Overview presence, and ranks the things that are surging, new or over-indexing in the chosen segment. Marketers, merchandisers and content planners use it to find next-quarter openings and risks. Data comes from the ListeningMind Data API (trend_finder, intent_finder, keyword_info, SERP, path_finder, cluster_finder). Markets: Korea, Japan, US; the gender and age split exists only for Korea.

Korean: 성별·연령 세그먼트에서 지금 검색이 뜨는 것은 무엇인가 · Japanese: 性別・年齢セグメントでいま検索が伸びているものは何か

## Use it as an agent
- [MCP server](https://daas-pulse.listeningmind.ai/mcp): Streamable HTTP, JSON-RPC. 20 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-pulse.listeningmind.ai/.well-known/openapi.json): the same tools as a REST contract (operationId = tool name)
- [agents.md](https://daas-pulse.listeningmind.ai/agents.md): step-by-step guide · [API catalog](https://daas-pulse.listeningmind.ai/.well-known/api-catalog) · [MCP server card](https://daas-pulse.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-pulse.listeningmind.ai/_lm/auth/signup); other changes over MCP need the member's agent key (LM-User-Key header, created at https://daas-pulse.listeningmind.ai/_lm/account)

## What you give and what you get
- Inputs: Segment (gender all/f/m, age a13 to a50), categories (beauty, food, ...) or seed keywords (comma separated, e.g. sunscreen, cushion), period (1m/3m/6m/12m), market (kr/jp/us), purpose (discover, campaign, ...), and optionally a plain-language brief, things to exclude and a credit cap.
- Outputs: Ranked entities, tabs for surging, emerging, newcomers and over-indexing keywords, scores with evidence per keyword, harvest coverage and credit log. Keyword drill-down (search paths, clusters, SERP narrative) and keyword brief (Markdown, HTML, PDF). Report as HTML or Markdown, trends CSV, result JSON.
- Cost: A run costs roughly 1,000-15,000 Data API credits (server cap 15,000; cached calls are free) plus LLM classification calls, and takes 2-3 minutes. A keyword drill-down costs about 3,830 credits (standard) or 5,480 (deep). Seed suggestions about 260 credits. Reading a brief is one LLM call.

## How a result is made (in order)
1. `get_config`: Get valid categories, purposes, segments and the credit cap.
2. `interpret_brief`: If there is a written request, turn it into run parameters.
3. `suggest_seeds`: With a single seed, add seeds that open other demand clusters.
4. `estimate_credits`: Check the expected credits and tell the person before starting.
5. `start_run`: Start the run.
6. `get_run`: Poll until status is done, then read the result.
7. `get_run_evidence`: Check coverage and the credit log behind the result.
8. `explain_keyword`: Drill into a keyword of interest to see why it rises.
9. `get_keyword_brief_markdown`: Get the brief for the drilled keyword.
10. `get_report_markdown`: Get the full report as text.
11. `download_trends_csv`: Export the table as CSV.

Run stages reported by the app: seeds → harvest.issues → harvest.intent → harvest.serp → harvest.reharvest → harvest.measure → harvest.hop1 → harvest.hop2 → harvest.done → screen → screen.done → widen → classify → entities → formation → done

## Method (how the analysis works)
1. Choose seed keywords from the given seeds or categories (a written request can be turned into run parameters).
2. Harvest candidate keywords from the issue index (trend_finder), related queries (intent_finder) and topics mined from SERP and AI Overview.
3. Fetch gender and age share and 48-month volume for each candidate, and widen the harvest if too few pass the floor.
4. Classify type and fit with an LLM and group the queries into the things (entities) they name.
5. Measure when co-searched terms formed and rank the things that are surging, emerging, new or over-indexing in the segment.

## Reading the result
- entities is the ranked list of things; the trending (surging), emerging, newcomers and overindex tabs give scores and evidence per keyword.
- Over-indexing compares the segment's share with baseline_share; segment share is estimated from the gender and age marginals and exists only for Korea.
- coverage (measured pool size, demography_rate) and the credit log from get_run_evidence show how widely the result was measured.
- explain_keyword shows why one keyword rises, from search paths, co-search clusters and SERP.

## Requests this app answers well
- What is surging in beauty right now among women in their 20s in Korea
- Find food keywords newly rising among men in their 30s for next quarter's campaign
- Rank what has been emerging over the last 3 months from the seeds sunscreen and cushion
- List newly appearing search topics in home interior in the US and why they rise

## Continue in another app
- [Demand Forecast](https://daas-forecast.listeningmind.ai/llms.txt) (MCP `https://daas-forecast.listeningmind.ai/mcp`): When a rising item looks worth acting on and you need its next 3-6 months of demand and the launch or campaign timing. Carry: The rising keywords or entity names as seeds (up to 5), with the market.
- [CEP Finder](https://daas-cep.listeningmind.ai/llms.txt) (MCP `https://daas-cep.listeningmind.ai/mcp`): When you need to know in which situations people start looking for the rising item. Carry: The rising keyword and market.

## 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
- `get_config` (read, GET /api/config): Returns the option lists the input form uses: markets, categories per market, genders, ages, periods, purposes, credit cap, drill-down cost, and the current account credit balance. Free.
- `interpret_brief` (run, POST /api/interpret): Turns a plain-language request into run parameters (gender, age, category, seeds, period, purpose) and returns each field with the phrase it came from and the fields it could not read. One paid LLM call, no Data API credits, a few seconds. Fields not supported by the text stay null.
- `suggest_seeds` (run, POST /api/suggest_seeds): Proposes extra seed keywords that open different demand clusters than the given one, for the chosen segment. Uses intent_finder and keyword_info plus one LLM call. About 260 Data API credits (cap 780); the fetched data is cached and reused by the run. Takes 10-40 seconds.
- `estimate_credits` (read, POST /api/estimate): Returns a rough Data API credit estimate for the given run parameters ({credits}). Computed locally, no API calls. Cached calls in the real run cost nothing, so the actual spend is often lower.
- `start_run` (run, POST /api/runs): Starts a background run that harvests candidate keywords from the seeds, measures segment share and 48-month volume, classifies them with an LLM and ranks surging, emerging, newcomer and over-indexing things for the segment. Returns {run_id, url}. Poll get_run until status is done or error. Typically 2-3 minutes and roughly 1,000-15,000 Data API credits (capped by credit_cap).
- `get_run` (read, GET /api/runs/{run_id}): Returns one run: status (running, done, error), progress {stage, pct, steps}, credits spent, params and, when done, the full result (entities, trending, emerging, newcomers, overindex, harvest, coverage). Repeat until status is done or error.
- `list_runs` (read, GET /api/runs): Lists recent runs with run_id, status, credits, created_at, url, segment label, category, free_text, period and market.
- `get_run_evidence` (read, GET /api/runs/{run_id}/evidence): For a finished run, returns Data API calls per endpoint (calls, credits, cache hits), harvest and coverage details, skipped items, baseline share, score weights and seeds. Free.
- `explain_keyword` (run, POST /api/runs/{run_id}/explain): Explains why one keyword or entity from a finished run is rising: search paths, co-search clusters and SERP, summarised by an LLM with numbers checked against the data. standard costs about 3,830 Data API credits, deep (adds a 6-month path comparison) about 5,480. The result is stored, so asking again is free. 20-90 seconds.
- `get_keyword_brief_markdown` (read, GET /api/runs/{run_id}/brief.md): Returns {keyword, markdown}: a one-page brief for a keyword that was already drilled into with explain_keyword. Renders stored data only, no credits. 404 if the drill-down was not run.
- `get_keyword_brief_html` (read, GET /runs/{run_id}/brief.html): Returns the printable HTML page of a keyword brief (needs explain_keyword first). download=1 adds an attachment header. Free.
- `download_keyword_brief_pdf` (read, GET /runs/{run_id}/brief.pdf): Downloads the keyword brief as a PDF (needs explain_keyword first). Returns 503 when the server has no headless Chrome; then use get_keyword_brief_html. Free.
- `get_report_markdown` (read, GET /runs/{run_id}/report.md): Returns the full run report as Markdown text. Free. 404 until the run is done.
- `get_report_preview` (read, GET /runs/{run_id}/preview.html): Returns the full run report as an HTML page for viewing. Free.
- `download_report_html` (read, GET /runs/{run_id}/report.html): Downloads the full run report as a self-contained HTML file. Free.
- `download_trends_csv` (read, GET /runs/{run_id}/trends.csv): Downloads the ranked trend rows as CSV (UTF-8 with BOM). Free.
- `download_run_json` (read, GET /runs/{run_id}/run.json): Returns the raw result object of a finished run as JSON. Free.
- `rerun_run` (run, POST /api/runs/{run_id}/rerun): Starts a new run with the same parameters as an earlier run. Returns {run_id, url, from}. Same cost and duration as start_run, minus cached calls.
- `delete_run` (delete, DELETE /api/runs/{run_id}): Deletes a run and its stored drill-downs. Cannot be undone.
- `get_report_robots` (read, GET /_lm/report-robots/{run_id}): Returns whether search engines may index this report page (index or noindex), and why: a company member's run or one set by hand is index; a customer's run, and any run that is still going, failed or came back empty, is noindex. Read only; no credits.

## Pages
- [Pulse Finder home](https://daas-pulse.listeningmind.ai/): Run form and run history.
- [Method](https://daas-pulse.listeningmind.ai/method): How the Trend Score is computed. With ?run=<run_id> it decomposes that run's top keyword.

## Limits
- Gender and age split only works for gl=kr; jp and us are market-wide. Segment share is derived as the product of the gender and age marginal distributions. UI languages ko/ja/en. A keyword brief exists only after explain_keyword ran for that keyword. Up to 6 seeds by default (max_seeds).

## 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`)
- [Creative Finder](https://daas-creative.listeningmind.ai/llms.txt): Finds purchase situations (CEP) in search data and drafts a creative, an image and a video for each (MCP `https://daas-creative.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`)
- [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