analytics-insights
Drive Google Analytics (GA4), Google Tag Manager, Google Search Console, and BigQuery from chat — tracking plans, GA4 reports, key-event (conversion) setup, custom dimensions and metrics, GTM audits, GSC performance, and GA4 BigQuery export queries. Use when the user wants an analytics audit, a GA4 report, a tracking plan, conversion setup, GTM cleanup, search-performance data, or asks "how is the site performing?" or "are my conversions firing?".
Works with
---
name: analytics-insights
description: Drive Google Analytics (GA4), Google Tag Manager, Google Search Console, and BigQuery from chat — tracking plans, GA4 reports, key-event (conversion) setup, custom dimensions and metrics, GTM audits, GSC performance, and GA4 BigQuery export queries. Use when the user wants an analytics audit, a GA4 report, a tracking plan, conversion setup, GTM cleanup, search-performance data, or asks "how is the site performing?" or "are my conversions firing?".
license: MIT
---
# Analytics Insights
Operator skill for the Google measurement stack — GA4, GTM, Search Console, and BigQuery — driven directly from chat. Build a tracking plan, run reports, mark conversions, audit existing setup, and query the warehouse without leaving the conversation.
## Out of scope — defer to other skills
| Request | Send them to |
| --- | --- |
| Keyword research, AI-search visibility, full SEO audit | `seo-research` (HyperSEO toolkit — broader and richer than GSC for keyword work) |
| Google Ads campaign performance | `google-ads` (campaign-level) — but GA4-side conversion attribution lives here |
| Meta / Facebook ads metrics | `meta-ads` |
| Email program metrics | `email-lifecycle` (provider-side) |
GSC and HyperSEO overlap on search-performance data. Rule of thumb: use GSC here for *the user's own site's* impression / click / position data. Use HyperSEO (in `seo-research`) for keyword research, competitor data, AI-search visibility.
## Requirements
- **Hyper MCP installed and connected.** [https://app.hyperfx.ai/mcp](https://app.hyperfx.ai/mcp)
- **At least one of these connected** at [https://app.hyperfx.ai/apps](https://app.hyperfx.ai/apps):
- **Google Analytics** — GA4 reports, custom metrics / dimensions, key-event (conversion) management.
- **Google Tag Manager** — tag / trigger / variable / workspace / version management.
- **Google Search Console** — search-performance data, sitemaps, URL inspection.
- **BigQuery** — SQL queries against the GA4 export (or any other dataset).
If `google_analytics_run_ga4_report`, `gtm_tag`, `google_search_console_get_performance_data`, and `bigquery_execute_query` are all missing from the agent's tool list, stop and tell the user to enable the Hyper MCP and connect at least one of these integrations.
## Tool surface
| Group | Tools |
| --- | --- |
| GA4 — reporting | `google_analytics_run_ga4_report`, `google_analytics_list_accounts`, `google_analytics_list_properties`, `google_analytics_get_property` |
| GA4 — properties & data streams | `google_analytics_create_ga4_property`, `google_analytics_update_property`, `google_analytics_delete_property`, `google_analytics_create_data_stream`, `google_analytics_list_data_streams`, `google_analytics_get_data_stream`, `google_analytics_update_data_stream`, `google_analytics_delete_data_stream`, `google_analytics_get_data_retention_settings` *(read-only — no update variant in MCP)*, `google_analytics_acknowledge_user_data_collection` |
| GA4 — key events (conversions) | `google_analytics_create_key_event`, `google_analytics_list_key_events`, `google_analytics_get_key_event`, `google_analytics_update_key_event`, `google_analytics_delete_key_event` |
| GA4 — custom metrics / dimensions | `google_analytics_create_custom_metric`, `google_analytics_list_custom_metrics`, `google_analytics_get_custom_metric`, `google_analytics_update_custom_metric`, `google_analytics_archive_custom_metric`, `google_analytics_create_custom_dimension`, `google_analytics_list_custom_dimensions`, `google_analytics_get_custom_dimension`, `google_analytics_update_custom_dimension`, `google_analytics_archive_custom_dimension` |
| GTM (note: prefixed `gtm_*`, **not** `google_tag_manager_*`) | `gtm_account`, `gtm_container`, `gtm_workspace`, `gtm_tag`, `gtm_trigger`, `gtm_variable`, `gtm_built_in_variable`, `gtm_folder`, `gtm_environment`, `gtm_version`, `gtm_version_header`, `gtm_user_permission`, `gtm_client`, `gtm_template`, `gtm_transformation`, `gtm_zone`, `gtm_destination` |
| Google Search Console | `google_search_console_get_performance_data`, `google_search_console_list_sites`, `google_search_console_list_sitemaps`, `google_search_console_get_sitemap`, `google_search_console_submit_sitemap`, `google_search_console_delete_sitemap`, `google_search_console_submit_url` |
| BigQuery | `bigquery_execute_query`, `bigquery_insert_rows` |
## Critical rules
1. **GA4 property IDs — arg name differs by tool.** Three patterns: (a) Reporting tools (`run_ga4_report`, `get_property`) take `property_id="properties/123456789"`. (b) Create and list tools (`create_key_event`, `list_key_events`, `create_custom_dimension`, `list_custom_dimensions`, etc.) take `parent="properties/123456789"`. (c) Get/update/delete tools operate on a specific resource and take `name=` with the full resource path (e.g. `"properties/123456789/keyEvents/12345"`). All three need the `properties/` prefix in some form — passing a bare numeric ID silently fails. When in doubt, check the tool's schema for which arg is marked `required`.
2. **Date ranges are inclusive on both ends.** `start_date="2026-04-01"` and `end_date="2026-04-30"` returns 30 days, not 29. Same for relative dates: `7daysAgo` to `today` is 8 days, not 7.
3. **GA4 sampling kicks in above ~10M events.** For high-volume properties, the GA4 API silently samples results. If precision matters (board reporting, financial attribution), use the **BigQuery GA4 export** instead — see [`references/bigquery-ga4-export.md`](./references/bigquery-ga4-export.md).
4. **Conversions in GA4 are "key events".** GA4 renamed "conversions" to "key events" in 2024. The tools reflect this — use `google_analytics_create_key_event` to mark an event as a conversion. Don't get confused by older docs.
5. **GTM changes need a workspace + version + publish.** Tags / triggers / variables created in a workspace are *not live* until the workspace is committed to a new version and that version is published. Use `gtm_workspace` → modify → `gtm_version` (create) → publish.
6. **GSC data has a 2–3 day lag.** Don't query "yesterday" in GSC and expect data — query 3+ days back for stable numbers. GA4 has a 24-48h lag for some metrics.
7. **Apple Mail Privacy Protection inflates GA4 "engaged" sessions from email.** Don't trust email-driven engagement numbers in GA4 alone — cross-reference with the email provider's own click data.
## Workflow — pick the right path
The skill covers four distinct jobs. Pick first; the workflows are different.
| The user wants… | Path | Reference |
| --- | --- | --- |
| A report ("how did we do last month?") | Phase R | — |
| To set up tracking ("we need to measure X") | Phase T | [`references/ga4-tracking-plan.md`](./references/ga4-tracking-plan.md) |
| To audit existing GTM / GA4 ("why is conversion data wonky?") | Phase A | [`references/gtm-audit.md`](./references/gtm-audit.md) |
| Precise / unsampled / cross-source analysis | Phase B | [`references/bigquery-ga4-export.md`](./references/bigquery-ga4-export.md) |
### Phase R — Run a report (most common path)
**Quick-read option:** For instant, no-sampling queries against cached GA4 data, try `google_analytics_query_insights` first — it's faster than the full API path and avoids the ~10M-event sampling threshold. Call it with a `query=` SQL string; the tool description lists available columns and the cached table name. If it returns `"No data cached"`, read the `suggestion` field for the workspace-specific table name and retry. For cached GSC data, use `google_search_console_query_insights` with the same pattern. Fall through to Step 4 below for metrics not in the cache.
1. **Confirm the property.** `google_analytics_list_accounts()` → `google_analytics_list_properties(filter="parent:accounts/<account_id>")`. Ask the user to pick if there are multiple. Save the `properties/<id>` for the rest of the conversation.
2. **Pick the date range.** Always confirm. "Last 30 days" is `start_date="30daysAgo"`, `end_date="yesterday"` (avoid `today` — partial-day data is unstable).
3. **Pick metrics + dimensions.** Don't blast 12 metrics × 6 dimensions in one report — the result is unreadable. Pick the 2–3 metrics that answer the user's question and the 1–2 dimensions that segment them meaningfully.
4. **Run the report.**
```
google_analytics_run_ga4_report(
property_id="properties/123456789",
start_date="30daysAgo",
end_date="yesterday",
metrics=["activeUsers", "sessions", "conversions", "totalRevenue"],
dimensions=["sessionDefaultChannelGroup", "deviceCategory"],
)
```
5. **Present results as a table.** Always show the raw numbers alongside any interpretation. "Organic search drove 12,400 sessions (+18% MoM)" beats "organic was up."
6. **One follow-on if the data flags it.** If a metric stands out (e.g., conversion rate dropped 40% on mobile), run *one* targeted follow-up report — don't speculate.
#### Common GA4 metrics & dimensions
The GA4 API uses camelCase names. The most useful:
**Metrics:** `activeUsers`, `sessions`, `screenPageViews`, `bounceRate`, `engagementRate`, `averageSessionDuration`, `conversions`, `eventCount`, `totalRevenue`, `transactions`, `purchaseRevenue`, `userEngagementDuration`.
**Dimensions:** `country`, `city`, `deviceCategory`, `operatingSystem`, `browser`, `sessionDefaultChannelGroup`, `sessionSource`, `sessionMedium`, `sessionCampaignName`, `pagePath`, `eventName`, `date`, `hour`, `landingPage`.
For the full list, the user can browse the [GA4 Data API reference](https://developers.google.com/analytics/devguides/reporting/data/v1/api-schema).
### Phase T — Set up tracking
The GA4 API can create properties, data streams, key events, custom metrics, and custom dimensions — but it **can't deploy GTM tags into the page**. That step is GTM-side (or hard-coded in the site). The skill workflow:
1. **Tracking plan first.** Define what events you need to fire, where they fire, and which ones are conversions (key events). Full template in [`references/ga4-tracking-plan.md`](./references/ga4-tracking-plan.md).
2. **GA4-side setup** — create custom dimensions / metrics, mark key events:
```
google_analytics_create_custom_dimension(
parent="properties/123456789",
parameter_name="plan_tier",
display_name="Plan Tier",
scope="EVENT",
)
google_analytics_create_key_event(
parent="properties/123456789",
event_name="purchase",
counting_method="ONCE_PER_EVENT",
)
```
3. **GTM-side setup** — create/update tags + triggers + variables in a workspace, then version + publish:
```
gtm_workspace(operation="create", account_id="...", container_id="...", name="purchase-tracking-v3")
gtm_tag(operation="create", workspace_path="...", tag_definition={...})
gtm_trigger(operation="create", workspace_path="...", trigger_definition={...})
gtm_variable(operation="create", workspace_path="...", variable_definition={...})
gtm_version(operation="create", workspace_path="...", version_name="purchase-tracking-v3")
# then publish via the GTM UI or version operation
```
4. **Validate** — see Phase A.
### Phase A — Audit (the existing setup is broken or suspect)
Most "our analytics is wrong" complaints are one of:
| Symptom | Likely cause | How to confirm |
| --- | --- | --- |
| Conversion event not appearing in GA4 | Event firing in GTM but not reaching GA4 (wrong measurement ID, blocked by consent gate, ad blocker) | `google_analytics_run_ga4_report` for `eventName=purchase` over the last 7d → if 0, check GTM |
| Conversion count wildly off | Event firing on every page (not just confirmation), or duplicate tags | Audit GTM tags via `gtm_tag(operation="list")`, check for multiple tags firing on the same trigger |
| Revenue reported differently in GA4 vs the platform of record | Currency mismatch, refund handling, attribution window | Pull both side-by-side, look for refund / currency rows |
| Suddenly mobile traffic dropped to ~0 | Tag firing only on desktop trigger, or a recent GTM publish broke the mobile container | `gtm_version(operation="list")` to find recent publishes, diff with previous version |
| GSC clicks ≠ GA4 organic sessions | Always different — different definitions. Don't try to reconcile exactly. | Expected; document and move on |
Detailed audit walkthrough in [`references/gtm-audit.md`](./references/gtm-audit.md).
### Phase B — BigQuery GA4 export (precision / cross-source analysis)
For unsampled data, custom attribution, joining GA4 with order-DB / CRM data, or cohort analysis. Requires the GA4 → BigQuery export to be turned on in the GA4 admin (free for standard properties since 2023).
```
bigquery_execute_query(
query="""
SELECT
event_date,
COUNT(DISTINCT user_pseudo_id) AS users,
COUNTIF(event_name = 'purchase') AS purchases,
SUM(IF(event_name = 'purchase', ecommerce.purchase_revenue, 0)) AS revenue
FROM `your-project.analytics_123456789.events_*`
WHERE _TABLE_SUFFIX BETWEEN '20260401' AND '20260430'
GROUP BY event_date
ORDER BY event_date
"""
)
```
Schema, common queries, and the full attribution-modeling workflow in [`references/bigquery-ga4-export.md`](./references/bigquery-ga4-export.md).
## Output standards
- **Always present numbers as tables**, not prose. "12,400 sessions, 8.2% bounce, 1.4% conversion" → markdown table.
- **Always include the date range** in the report header. "Apr 1–30, 2026" — undated numbers are useless.
- **Always include the property / site** the report came from. Multi-property organizations get burned by this constantly.
- **Annotate sampling.** If GA4 returns a `samplesReadCount < samplingSpaceSize`, say so explicitly. The user needs to know whether to trust the number for finance / board reporting.
- **Distinguish "ratio metric" from "summable metric".** Bounce rate, engagement rate, conversion rate are *ratios* and don't sum — present them as one number, not a column total.
## Reference workflows
| Reference | When to read |
| --- | --- |
| [`references/ga4-tracking-plan.md`](./references/ga4-tracking-plan.md) | Designing what to track — recommended event schema, custom dimensions / metrics, key-event mapping, naming conventions |
| [`references/gtm-audit.md`](./references/gtm-audit.md) | Auditing an existing GTM container — finding duplicate tags, broken triggers, unused variables, missing consent gates |
| [`references/bigquery-ga4-export.md`](./references/bigquery-ga4-export.md) | Querying the GA4 BigQuery export — schema, common queries (DAU, funnel, attribution, cohort, retention), join patterns |More SEO & Marketing skills
ai-video-generation
skills-101/superpowers
Generate AI videos with Google Veo, Seedance 2.0, HappyHorse, Wan, Grok and 40+ models via inference.sh CLI. Models: Veo 3.1, Veo 3, Seedance 2.0, HappyHorse 1.0, Wan 2.5, Grok Imagine Video, OmniHuman, Fabric, HunyuanVideo. Capabilities: text-to-video, image-to-video, reference-to-video, video editing, lipsync, avatar animation, video upscaling, foley sound. Use for: social media videos, marketing content, explainer videos, product demos, AI avatars. Triggers: video generation, ai video, text to video, image to video, veo, animate image, video from image, ai animation, video generator, generate video, t2v, i2v, ai video maker, create video with ai, runway alternative, pika alternative, sora alternative, kling alternative, seedance, happyhorse
ai-image-generation
skills-101/superpowers
Generate AI images with GPT-Image-2, FLUX, Gemini, Grok, Seedream, Reve and 50+ models via inference.sh CLI. Models: GPT-Image-2, FLUX Dev LoRA, FLUX.2 Klein LoRA, Gemini 3 Pro Image, Grok Imagine, Seedream 4.5, Reve, ImagineArt. Capabilities: text-to-image, image-to-image, inpainting, LoRA, image editing, upscaling, text rendering. Use for: AI art, product mockups, concept art, social media graphics, marketing visuals, illustrations. Triggers: flux, image generation, ai image, text to image, stable diffusion, generate image, ai art, midjourney alternative, dall-e alternative, text2img, t2i, image generator, ai picture, create image with ai, generative ai, ai illustration, grok image, gemini image, gpt image, openai image, chatgpt image
ai-avatar-video
skills-101/superpowers
Create AI avatar and talking head videos via inference.sh CLI. Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS). Also: OmniHuman, Fabric, PixVerse. Audio: Inworld TTS-2 (100+ languages, emotion steering for characters), ElevenLabs, Kokoro. Capabilities: audio-driven avatars, text-to-avatar, lipsync videos, talking head generation, virtual presenters, UGC content. Use for: AI presenters, explainer videos, virtual influencers, dubbing, marketing videos, UGC ads, gaming avatars, NPC dialogue. Triggers: ai avatar, talking head, lipsync, avatar video, virtual presenter, ai spokesperson, audio driven video, heygen alternative, synthesia alternative, talking avatar, lip sync, video avatar, ai presenter, digital human, ugc, ugc video, ugc ad, avatar ugc

