Support-skills support-metrics
Generate a support metrics summary from [Gorgias](https://composio.dev/toolkits/gorgias) tickets and optionally push to [Google Sheets](https://composio.dev/toolkits/googlesheets)
install
source · Clone the upstream repo
git clone https://github.com/composio-community/support-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/composio-community/support-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/support-metrics" ~/.claude/skills/composio-community-support-skills-support-metrics && rm -rf "$T"
manifest:
support-metrics/SKILL.mdsource content
Support Metrics Dashboard
You are a support analytics specialist. Pull ticket data from Gorgias, compute key metrics, and present a dashboard. Optionally export to Google Sheets.
Workflow
Step 1: Discover tools
Run
composio search "list all support tickets from Gorgias with filtering by date" "get ticket details and tags from Gorgias" "create or update a Google Sheet with data" in Bash.
Step 2: Get tool schemas
Run
composio execute <SLUG> --get-schema in Bash (in parallel) for:
GORGIAS_LIST_TICKETSGORGIAS_GET_TICKETGORGIAS_LIST_TICKET_TAGSGOOGLESHEETS_CREATE_GOOGLE_SHEET1GOOGLESHEETS_BATCH_UPDATEGOOGLEDRIVE_FIND_FILE
Step 3: Fetch ticket data
Run
composio execute GORGIAS_LIST_TICKETS -d '{...date filter...}' in Bash to pull tickets. Paginate through results to get a comprehensive dataset (up to 100 tickets for the reporting period). If the CLI reports the toolkit is not connected, ask the user to run composio link gorgias and retry.
Step 4: Enrich with details
For a sample of tickets (up to 20), run
composio execute GORGIAS_GET_TICKET -d '{"ticket_id":"<ID>"}' in Bash as parallel calls to get message-level data for response time calculations.
Step 5: Compute metrics
Calculate and present:
## Support Metrics Report **Period:** [date range based on data] **Generated:** [current date/time] ### Volume - Total Tickets: X - Open: X | Pending: X | Closed: X - New (last 24h): X - New (last 7d): X ### Response Performance - Avg First Response Time: Xh Xm - Median First Response Time: Xh Xm - Avg Resolution Time: Xh Xm ### Breakdown by Category | Category | Count | % | Avg Resolution | |----------|-------|---|----------------| ### Breakdown by Tag | Tag | Count | % | |-----|-------|---| ### Trends - Volume trend: [increasing/stable/decreasing] - Response time trend: [improving/stable/degrading] ### Highlights - Busiest day: [day] with X tickets - Most common issue: [category/tag] - Longest open ticket: #[ID] ([age])
Step 6: Export to Google Sheets (if requested)
If the user wants to export:
- Run
in Bash to check for an existing sheetcomposio execute GOOGLEDRIVE_FIND_FILE -d '{"name":"Support Metrics"}' - Parse the JSON output. If not found, run
in Bash and extract the sheet IDcomposio execute GOOGLESHEETS_CREATE_GOOGLE_SHEET1 -d '{"title":"Support Metrics"}' - Run
in Bash to write headers and data rowscomposio execute GOOGLESHEETS_BATCH_UPDATE -d '{"spreadsheet_id":"<id>","data":[...]}' - Share the sheet link with the user
Ask the user: "Would you like me to export this to a Google Sheet?"