Identify Employees

Identify employee traffic

Some Parse.ly customers tag their employees' pageviews in the tracker via extra_data (e.g., extra_data['Internal'] = true set on logged-in users). Parse.ly's dashboard uses that tag for segment filtering, but the DPL stream is raw – tagged events still arrive. This flow finds that tag (when present and unambiguous) and saves it to bucket.json. Subsequent staircase runs apply the filter automatically and surface a one-line note in the report.

Customers who use Parse.ly's account-level IP blocklist instead (the more common pattern) need nothing from this flow – their DPL events are already filtered upstream.

The user may ask to clear the saved filter instead of detecting one (e.g. "remove the employee filter", or the --clear argument on harnesses with slash commands).

Output discipline

Terse. The detection script prints its own one-line result; output it verbatim and stop.

Steps

0. Resolve the plugin root. Every bash snippet below assumes $plugin_root is set in that shell invocation; re-run this line whenever you start a new shell:

   plugin_root="${CLAUDE_PLUGIN_ROOT:-${CURSOR_PLUGIN_ROOT:-<plugin-root>}}"
   plugin_python="${AGENTIC_ANALYTICS_VENV:-${AGENTIC_ANALYTICS_DATA_DIR:-$HOME/.local/share/agentic-analytics}/venv}/bin/python"
   [ -x "$plugin_python" ] || plugin_python="python3"
   

   <plugin-root> is the plugin's install directory – the directory two levels above this SKILL.md file. In a dev checkout of the source repo that's plugin/. $plugin_python is the plugin's isolated venv (created by the init flow at $AGENTIC_ANALYTICS_DATA_DIR/venv, default ~/.local/share/agentic-analytics/venv); it falls back to python3 if the venv doesn't exist yet.

1. Load bucket config. Read ${XDG_CONFIG_HOME:-~/.config}/agentic-analytics/bucket.json. It contains:

   • bucket – S3 bucket holding the customer's DPL events.
   • cache_dir – a slug identifying the customer's data (e.g. acme).

   If the file is missing, tell the user to run the init flow first (/agentic-analytics:init on harnesses with slash commands, or "set up agentic analytics" in chat) and stop.

2. Handle a clear request. If the user asked to clear, remove any saved filter and stop:

   "$plugin_python" "$plugin_root/skills/identify-employees/scripts/detect_employee_filter.py" \
     --bucket-config "${XDG_CONFIG_HOME:-$HOME/.config}/agentic-analytics/bucket.json" \
     --clear
   

   Output the script's one-line result and stop.

3. Run detection. Otherwise sample events from the catalog and write any unambiguous filter to bucket.json. Pass --site <site> to scope the sample to a specific site (when the user provides one – via a slash-command argument on harnesses that have them, or in chat); omit it to sample across all sites:

   "$plugin_python" "$plugin_root/skills/identify-employees/scripts/detect_employee_filter.py" \
     --bucket-config "${XDG_CONFIG_HOME:-$HOME/.config}/agentic-analytics/bucket.json" \
     [--site <site>]
   

4. Output the script's one-line result verbatim. Three possibilities:

   • Match found: "Detected employee traffic tagged with extra_data['<key>'] = <value> (X% of N sampled pageviews). Will filter this out of audience reports so it doesn't skew your results. Tell me if this is incorrect."
   • No match: "No unambiguous employee-traffic tag detected in N sampled pageviews. No filter applied."
   • Lake empty: "No pageview events found in the lake[ for site '']. Run /agentic-analytics:staircase or /agentic-analytics:refresh-cache first." – tell the user to run the staircase report or the refresh-cache flow first to populate the lake, then re-run this flow.

   Don't add framing or summary.

Notes

• The filter is auto-applied only when unambiguous (matched case-insensitively): known key name in internal, is_internal, is_employee, employee, staff, internal_user/internalUser, internal_traffic; boolean-ish value (true/1/yes); and tagged share between 0.1% and 25% of sampled pageviews. Ambiguous setups (multiple distinct values on the same key, or a share outside that range) are silently skipped.
• Re-running this flow after the customer changes their tracker is the right way to refresh the detected filter.
• A clear request removes any saved filter and exits without scanning – useful when detection got the wrong key and you want to start over.
• This flow does not touch Parse.ly's per-account IP blocklist, which is the canonical mechanism for customers who go that route (managed by Parse.ly Support, applied upstream of the DPL).