Data & Analytics

patsnap Bundle

用于专利全景项目的环节2。它消费 patent-panorama-insights-search（环节1）产出的已验证 `search_config.json`、`candidate_pool.csv` 和 `core_recall.csv`，生成全景统计（趋势、申请人格局、技术构成、竞品画像）、按分支组织的核心专利索引（默认采信环节1召回排序，仅在必要时做有边界的兜底核查）和价值信号交叉挖掘文件。所有统计直接从检索式聚合，不需要逐件专利标引。

zhaobenxiang5-coder Bundle

Turn flow-task-center-pro AI商品上架包 / listing-upload-pack artifacts into a Dianxiaomi 店小秘上架 TEMU 半托管 product draft workflow or Excel bulk import pack. Use when the user asks for 店小秘上架, 店小秘铺货, 店小秘批量导入, 店小秘草稿测试, TEMU半托管补丁包, 店小秘图片上传, 1688采集到店小秘后用中台套图覆盖, or testing a Dianxiaomi listing workflow without publishing.

kakatur Skill

Design, implement, or review local hybrid search that combines metadata or SQL filtering with embedding similarity, persistent vector artifacts, stable record mapping, and reproducible ranking. Use for semantic retrieval over structured datasets, not for autonomous agents or generative-answer systems.

ruosong320 Bundle

对照法律原文审查 CSV 的忠实性及条款覆盖率；适用于法规结构化、拆行与重述结果核对。

mimmo-the-root Skill

Analizza i dati del Creator Portal e delle fonti pubbliche per migliorare CTR, retention, playtime e scoperta delle mappe Fortnite. Usa quando l'utente condivide metriche, chiede analisi di performance o vuole confrontare la propria mappa con i competitor.

ruosong320 Bundle

将 input_datas/{topic} 中的本地资料和 CSV 链接整合为中文纯节点 markmap；适用于要求完整阅读来源并构建主题知识树的任务。

tahr-security Bundle

Trace attacker-controlled input through parsing, validation, normalization, storage, and dangerous server or browser sinks, then safely validate exploitability with class-specific proof gates. Use for injection review, source-to-sink analysis, XSS, SQL/NoSQL injection, command or template injection, SSRF, XXE, path traversal, unsafe deserialization, file upload/processing, webhook, CORS/postMessage, or client-side trust-boundary testing.

rifteo Bundle

Complete GraphQL security testing methodology — introspection abuse and schema enumeration, field suggestion oracle (when introspection is disabled), query depth/batching DoS, alias-based rate limit bypass, injection through arguments (SQL/NoSQL/SSTI), broken object-level and field-level authorization (IDOR via mutations), CSRF via GET mutations and content-type bypass, subscription hijacking via WebSocket, circular fragment DoS, and mass assignment via mutations. Trigger when the user finds a /graphql endpoint, sees GraphQL queries in traffic, wants to test a GraphQL API for vulnerabilities, needs to enumerate a hidden schema without introspection, wants to bypass rate limits or brute-force credentials through GraphQL, or needs to escalate privileges through mutations.

yasir-khan-7 Bundle

Summarize a CSV file — row count, column types, missing values, and a preview table. Use when the user uploads a .csv and wants a quick overview before analysis.

ankit1598 Bundle

Enforces one-shot Node ESM Mongo ops under `.scripts/<scriptName>/` — dry-run default, `--apply` writes, colocated `output/`, always-on action log, undo-ready rows. Use when writing or running a `.scripts` job, backfill, heal, migrate, CSV reconcile, import, or data-fix script; when the user says "write a script" or mentions `--apply`, `--undo`, `--verbose`, dry-run. Not for app MongoClient pools, schema design, or query-index work.

agentcorp-inc Skill

Investigates a session recording by gathering metadata, person profile, same-session events, and linked error tracking issues in one pass. Use when a user provides a recording or session ID and wants to understand what happened — who the user was, what they did, what errors occurred, and whether there are related error tracking issues. Replaces the manual chain of session-recording-get, persons-retrieve, execute-sql, and query-error-tracking-issues-list.

agentcorp-inc Skill

Identify, measure, and exclude bot / crawler / AI-agent traffic in PostHog web and product analytics using the traffic classification surface (the isLikelyBot / getTrafficType HogQL functions and the $virt_* virtual properties). Use when the user asks to "exclude bots", "filter out crawlers", "remove bot traffic from my numbers", "how much of my traffic is bots / AI crawlers", "is GPTBot / ChatGPT / Claude hitting my site", "break down traffic by human vs bot", or wants clean human-only counts in an insight or dashboard. For the real-time Live tab bot tiles, use exploring-live-traffic instead.

agentcorp-inc Skill

Investigate individual PostHog MCP sessions — the sequence of tool calls a single agent made in one run, what it was trying to do, and where it went wrong. Use when the user asks "what did this MCP session do?", "show me the tool calls for session X", "what was the agent's goal?", "which sessions had errors?", or pastes an MCP analytics sessions URL.

steve-t-hill Bundle

Expert guidance and automated agent protocol for generating configuration and deployment artifacts for BigQuery Conversational Analytics (BQCA) Agents. This skill automates the creation of 'config.yaml', system instructions, agent-level glossaries, table schema metadata, join relationships, and Python-based synchronization scripts to enable NL2SQL and GQL capabilities against existing datasets and Property Graphs. Use this skill when: 1. Building a new conversational analytics agent from scratch. 2. Generating or updating system instructions, agent-level glossaries, or table relationships for an NL2SQL agent. 3. Scaffolding deployment scripts for BQCA lifecycle management.

arin117kaushik Bundle

Use when the user shares a Substack subscriber export or CSV, or wants to win back lapsed or cancelled readers, re-engage inactive subscribers, target a group of subscribers, plan segments or tags, or write a welcome email. Not for public Notes (use substack-notes-writer) or post stats (use substack-analytics-digest).

agentcorp-inc Skill

Use when the user asks about revenue, payments, subscriptions, billing, CRM deals, support tickets, ad spend, production database tables, or other data PostHog does not collect natively — or wants to join or correlate PostHog product events with that external business data. Also use when a query fails because a table does not exist or returns no results for expected external data. The data warehouse can import from SaaS tools (Stripe, Hubspot, Zendesk, etc.), ad platforms, production databases (Postgres, MySQL, BigQuery, Snowflake), and other arbitrary data sources. Covers checking existing sources, identifying the right source type, and guiding the setup.

agentcorp-inc Skill

Starting point for exploring how a PostHog MCP server's tools are used — routes a broad question to the typed tool that answers it. Use when the user asks "how is my MCP doing?", "what should I look at?", "explore my tool calls", "who uses my MCP tools?", "what are agents doing with the MCP?", or pastes an MCP analytics URL without a specific question. Offers a menu of questions, each backed by a query tool, then hands off to the focused skill.

agentcorp-inc Bundle

Add PostHog LLM analytics to trace AI model usage. Use after implementing LLM features or reviewing PRs to ensure all generations are captured with token counts, latency, and costs. Also handles initial PostHog SDK setup if not yet installed.

agentcorp-inc Skill

Investigate the quality of PostHog MCP tool calls — error rates, latency, reach, and which tools are failing or slow. Use when the user asks "which MCP tool has the highest error rate?", "what's the slowest tool?", "which tools fail most often?", "how reliable is tool X?", wants a tool-quality matrix, or pastes an MCP analytics tool-quality / dashboard URL and asks what it shows.

agentcorp-inc Bundle

Diagnoses bias, anomalies, and strange-looking results on a specific PostHog experiment. Covers empty / 0-exposure experiments, sample ratio mismatch, identity fragmentation, multi-variant exposure, uneven-split exclusion bias, significance traps (peeking, A/A, Bayesian vs Frequentist), PostHog-vs-SQL discrepancies, and surprises after mid-run edits. Symptom-driven dispatch to the right diagnostic. TRIGGER when: user asks 'is my experiment biased?' or 'why 0 exposures?', references the bias banner, says a variant looks strange / wrong / off, sees significance flipping, notices PostHog numbers disagreeing with their SQL, sees an A/A test showing significance, or reports surprises after mid-run edits. DO NOT TRIGGER when: creating a new experiment (use creating-experiments), only configuring rollout (use configuring-experiment-rollout) or metrics (use configuring-experiment-analytics), or only asking lifecycle questions (use managing-experiment-lifecycle).

agentcorp-inc Skill

Explore PostHog MCP intent clusters — agent goals grouped by semantic similarity, with each cluster's tool distribution and error rates. Use when the user asks "what are agents trying to do with the MCP?", "group the intents", "which goals fail most?", "what does each cluster route to?", wants to recompute the clustering, or pastes an MCP analytics intent-clustering URL.

agentcorp-inc Skill

Signals scout for PostHog web traffic. Watches per-channel session volume, attribution breakage, and landing-page health (bounce / 404 steps) against the site's own baseline, and files each validated divergence as a report in the inbox. Per-page web vitals have their own dedicated `signals-scout-web-vitals`.

agentcorp-inc Bundle

Add PostHog product analytics events to track user behavior. Use after implementing new features or reviewing PRs to ensure meaningful user actions are captured. Also handles initial PostHog SDK setup if not yet installed.

agentcorp-inc Skill

Guides agents through the 3-step experiment creation flow: defining the hypothesis, configuring rollout, and setting up analytics. Delegates rollout decisions to configuring-experiment-rollout and metric setup to configuring-experiment-analytics. TRIGGER when: user asks to create a new experiment or A/B test, OR when you are about to call experiment-create. DO NOT TRIGGER when: user is updating an existing experiment, managing lifecycle, or only browsing experiments.

agentcorp-inc Bundle

ABSOLUTE MUST to debug and inspect LLM/AI agent traces using PostHog's MCP tools. Use when the user pastes a trace or session URL (e.g. /ai-observability/traces/<id> or /ai-observability/sessions/<id>), asks to debug a trace, figure out what went wrong, check if an agent used a tool correctly, verify context/files were surfaced, inspect subagent behavior, investigate LLM decisions, or analyze token usage and costs. Also use when raw SQL/HogQL against `events.properties.$ai_input` / `$ai_output_choices` returns empty — message content lives only on the dedicated `posthog.ai_events` table.

agentcorp-inc Skill

Guides experiment state transitions: launching, pausing, resuming, ending, shipping variants, archiving, resetting, duplicating, and copying to another project. Covers preconditions, implications for variant assignment and analysis, and the decision framework for when to use each action. TRIGGER when: user asks to launch, pause, resume, end, ship, archive, reset, duplicate, or copy an experiment to another project. DO NOT TRIGGER when: user is creating an experiment (use creating-experiments), configuring rollout (use configuring-experiment-rollout), or setting up metrics (use configuring-experiment-analytics).

agentcorp-inc Skill

Export PostHog events, persons, or sessions on demand and download the resulting files. Use when the user asks to download/export raw PostHog data, create a one-off file export, fetch a Parquet or JSONLines export, or use the file_download_batch_exports API. Covers starting the export with MCP, polling completion, and downloading via the existing REST redirect endpoint.

agentcorp-inc Skill

Signals scout for core product-analytics flows — funnels, retention, lifecycle, stickiness, and paths. Watches the team's saved flows for a derived-rate regression (conversion or retention sliding) while entrants hold, and files it as a report in the inbox.

agentcorp-inc Skill

Signals scout for PostHog revenue analytics. Watches for upstream failures (Stripe sync stalls, capture regressions), config drift, and goal-miss escalations, and files each validated finding as a report in the inbox.

agentcorp-inc Bundle

Configures the analytics side of a PostHog experiment — exposure criteria (default `$feature_flag_called` vs custom exposure events), primary and secondary metrics, the supported metric types (count, sum, ratio with `math` and `math_property`, retention with `retention_window_start` and `start_handling`), multivariate user handling ("Exclude" vs "First seen variant"), and how to read results once the experiment is live. Use when the user adds or edits a primary or secondary metric (e.g. "add a secondary metric tracking 'downloaded_file' per user"), sets up a ratio metric (e.g. "revenue from purchase_completed / pageviews"), sets up a retention metric (e.g. "$pageview → uploaded_file, 7-day window"), configures custom exposure (e.g. "only count users who hit /checkout"), changes multivariate handling, or asks "who is in the analysis?", "how do I measure impact?", "is this winning?", "what's the confidence level?", or "should I ship?".

agentcorp-inc Skill

Inspects URL paths and proposes, tests, orders, and applies project-level path cleaning rules so dynamic segments (numeric IDs, UUIDs, slugs, dates) collapse into readable aliases. Use when the user says "clean the paths", "normalize URLs", "group similar pages", "too many distinct paths", "/users/123 and /users/456 are the same page", "set up path cleaning", or asks why a Web analytics or Paths breakdown is fragmented across thousands of nearly-identical URLs. Covers regex syntax (re2), alias placeholder convention, rule ordering, the test workflow, and applying rules via the project-settings-update MCP tool.

agentcorp-inc Skill

Focused Signals scout for PostHog projects importing external data into the warehouse. Watches the import side — external data sources, their per-table sync schemas, webhook push channels, and materialized views — for the moments an import quietly stops keeping its promise: a source connection in Error (cascading to every table under it), a schema Failed or stuck Running, a schema that reads Completed but has fallen behind its own sync cadence (a silent, growing data gap), a webhook push channel broken behind a green status, a row-volume cliff, and failed or abandoned materialized views. Files each validated import contradiction as a report in the inbox; otherwise writes durable memory and closes out empty. Self-contained peer in the signals-scout-* fleet.

agentcorp-inc Bundle

Converts engineering analytics (PR / CI) data into saved PostHog insights, dashboards, and subscriptions, and explains what data the product reads so it can be queried directly with SQL. The engineering analytics dashboard and MCP tools run curated HogQL privately over per-team GitHub warehouse tables; this skill teaches discovering those tables via engineering-analytics-sources, replicating the curated column semantics in HogQL, saving the query with insight-create, and scheduling delivery with subscriptions-create. Use when asked to "save this as an insight", "put CI health / merge times on a dashboard", "email me PR throughput weekly", "subscribe to these numbers", "alert on CI success rate", or "what data/tables does engineering analytics read". For ad-hoc CI and merge questions use diagnosing-ci-and-merge-bottlenecks instead.

agentcorp-inc Skill

Signals scout for PostHog Customer analytics (Accounts). Watches per-account engagement for churn-risk shapes — engagement cliffs, dormancy, champion departure — and the expansion inverse, weighted by commercial ownership, and files each validated risk as a report in the inbox.

agentcorp-inc Skill

Diagnose why a data warehouse sync is failing and recommend the right recovery action. Use when the user asks "why isn't my Stripe/Postgres/Hubspot sync working?", "this table has been stuck for hours", "the data in the warehouse looks wrong", or wants to troubleshoot a specific source or schema. Covers source-level vs schema-level failures, stuck Running states, credential and schema-drift errors, incremental-field misconfig, CDC prerequisite failures, and the cancel / reload / resync / delete-data recovery actions.

jakeschincariol Bundle

Read a YouTube Studio audience-retention export and find where viewers actually leave, then say what to change. Use for "why do people stop watching", "my retention is bad", a pasted retention chart or CSV, or "fix my pacing".