{ "openapi": "3.0.1", "info": { "title": "Reddit Topic Watcher - Intent, Sentiment, B2B Triggers, MCP", "description": "Reddit monitoring with intent classification (recommendation/comparison/alternative-seek/complaint), sentiment, B2B trigger scoring, author profile signals (karma, age, bot filter), competitor mention tracking, MCP-ready output. For SDR teams, brand monitoring, AI agents.", "version": "0.1", "x-build-id": "f1mrrkez03a7uTjpJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seibs.co~reddit-topic-watcher/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seibs.co-reddit-topic-watcher", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seibs.co~reddit-topic-watcher/runs": { "post": { "operationId": "runs-sync-seibs.co-reddit-topic-watcher", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seibs.co~reddit-topic-watcher/run-sync": { "post": { "operationId": "run-sync-seibs.co-reddit-topic-watcher", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "topic_watch", "brand_mention", "subreddit_dump", "user_profile" ], "type": "string", "description": "topic_watch: monitor N keywords across M subreddits. brand_mention: track a primary brand + competitor list with mention counts, sentiment split, top mentioning subs. subreddit_dump: pull latest posts from each subreddit (no keyword filter). user_profile: enrich a list of usernames with karma + account age signals.", "default": "topic_watch" }, "keywords": { "title": "Keywords / search queries", "type": "array", "description": "Search queries used in topic_watch and brand_mention modes. In brand_mention, the FIRST entry is treated as the primary brand. Examples: ['best CRM alternative', 'HubSpot vs Salesforce'].", "items": { "type": "string" } }, "subreddits": { "title": "Subreddits", "type": "array", "description": "Subreddit names without the r/ prefix. Leave empty in topic_watch / brand_mention to search across all of Reddit. Example: ['sales', 'saas', 'marketing'].", "items": { "type": "string" } }, "competitor_names": { "title": "Competitor names (brand_mention mode)", "type": "array", "description": "List of competing brand names to count alongside the primary brand. Mentions are case-insensitive whole-word matches. Example: ['Salesforce', 'HubSpot', 'Pipedrive'].", "items": { "type": "string" } }, "usernames": { "title": "Usernames (user_profile mode)", "type": "array", "description": "Reddit usernames to enrich (without u/ prefix). Returns karma, account age, mod/verified flags, plus a probable-bot indicator for very new low-karma accounts.", "items": { "type": "string" } }, "lookback_days": { "title": "Lookback window (days)", "minimum": 1, "maximum": 365, "type": "integer", "description": "Drop posts older than this many days. Reddit search returns up to ~1000 results regardless; this filters post-fetch.", "default": 30 }, "min_score": { "title": "Minimum post score", "minimum": 0, "type": "integer", "description": "Drop posts/comments with Reddit score below this. Filters out junk and downvoted threads.", "default": 5 }, "min_comments": { "title": "Minimum comment count", "minimum": 0, "type": "integer", "description": "Drop posts with fewer comments than this. Use to focus on engaged threads.", "default": 0 }, "min_author_karma": { "title": "Minimum author karma", "minimum": 0, "type": "integer", "description": "Drop posts whose author has less combined karma than this. Requires include_author_profiles=true to take effect; otherwise ignored.", "default": 0 }, "min_author_account_age_days": { "title": "Minimum author account age (days)", "minimum": 0, "type": "integer", "description": "Drop posts whose author's account is younger than this. Default 30 filters most bot accounts. Requires include_author_profiles=true; ignored otherwise.", "default": 30 }, "intent_filter": { "title": "Intent filter (emit only matching)", "uniqueItems": true, "type": "array", "description": "If set, only emit posts whose intent_classification matches one of these. Leave empty to emit all intents.", "items": { "type": "string", "enum": [ "question", "complaint", "recommendation_request", "comparison_request", "alternative_seek", "praise", "frustration", "neutral_discussion" ] }, "default": [] }, "min_b2b_trigger_score": { "title": "Minimum B2B trigger score (0-1)", "type": "string", "description": "Drop posts whose composite b2b_trigger_score is below this. Leave empty to emit all. Score combines intent type weight, recency, subreddit relevance, author quality. 0.7+ = high-intent SDR lead.", "default": "" }, "include_comments": { "title": "Fetch top comments per post", "type": "boolean", "description": "When true, fetches the top N comments for each emitted post and classifies sentiment + intent per comment. Adds latency but provides much richer signal.", "default": true }, "max_comments_per_post": { "title": "Max comments per post", "minimum": 0, "maximum": 50, "type": "integer", "description": "Cap on comments fetched per post. Ignored when include_comments is false.", "default": 10 }, "include_author_profiles": { "title": "Fetch author profiles", "type": "boolean", "description": "Fetch each post author's /about.json: karma, account age, mod/verified flags. Slower but enables bot filtering, karma filtering, and author_quality scoring. Cached per username across the run.", "default": false }, "output_format": { "title": "Output format", "enum": [ "json", "mcp", "csv_friendly" ], "type": "string", "description": "json: structured records (default; recommended for code). mcp: structured records PLUS topic_summary records with markdown-formatted summary blocks ready for LLM RAG / agent ingestion. csv_friendly: flattens nested fields and joins arrays with ' | ' for spreadsheet export.", "default": "json" }, "use_apify_proxy": { "title": "Use Apify Proxy", "type": "boolean", "description": "Route Reddit requests through Apify Proxy. Strongly recommended - Reddit blocks datacenter IPs aggressively.", "default": true }, "apify_proxy_groups": { "title": "Proxy groups", "type": "array", "description": "Apify Proxy groups. RESIDENTIAL is most reliable for Reddit. Defaults to RESIDENTIAL.", "default": [ "RESIDENTIAL" ], "items": { "type": "string" } }, "concurrency": { "title": "Concurrency", "minimum": 1, "maximum": 6, "type": "integer", "description": "Max parallel Reddit requests. Reddit allows ~60/min unauthenticated; default 4 stays well under that.", "default": 4 }, "max_results": { "title": "Max results per run", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Hard cap on total post records emitted. Comments and topic_summary records do not count against this.", "default": 200 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } }