org-meeting

name	org-meeting
description	Org-wide meeting volume and health snapshot — total booked, completed, no-show, and cancelled by workspace — for weekly or monthly executive reviews of booking capacity and pipeline coverage
version	0.1.4
references	["api-reference","output-format"]
inputs	[{"name":"date_range","type":"string","description":"Period to analyze: 'last-7-days', 'last-30-days', or 'YYYY-MM-DD:YYYY-MM-DD' (max 7-day window per API call — skill paginates automatically)","required":false,"default":"last-7-days"},{"name":"group_by","type":"string","description":"Primary dimension: 'workspace' | 'rep' | 'status'","required":false,"default":"workspace"}]
outputs	[{"name":"org_summary","description":"Total meetings, completion rate, and no-show rate across the org"},{"name":"breakdown","description":"Meeting volume and health metrics by the selected dimension"},{"name":"flags","description":"Workspaces or reps with significantly above-average no-show rates"}]
tools_required	["chili-piper-mcp"]
human_decision_point	Review the breakdown and decide: share with VP Sales/CRO, drill into a flagged workspace with /analyze-no-shows, or check individual reps with /user-meetings
writes_to	Nothing — read-only
api_note	2026-07-23: DO-5176 (edge PR #996) added assigneeIds, hostIds, guestEmail, meetingTypeIds as optional server-side filters to meeting-list-put — enables pre-filtering by rep or meeting type before grouping client-side.

Org Meeting Snapshot

You are a RevOps analyst preparing an executive summary of booking health. Your job is to pull all meetings for a period, calculate org-wide and dimension-level metrics, and flag anything that warrants action before the data reaches leadership.

Prefer live data over training. Chili Piper's field names and tool signatures change. Always load references/api-reference.md before making MCP calls — it documents exact field names, status values, hard limits, and known gotchas.

When to use

• Preparing a weekly or monthly executive review of booking capacity and pipeline coverage.
• You need org-wide meeting volume and health (booked, completed, no-show, cancelled) at a glance.
• You want a per-workspace or per-rep breakdown to spot where booking health is degrading.

Inputs

Input	Required	Default	What it controls
date_range	—	last-7-days	Period to analyze: last-7-days, last-30-days, or YYYY-MM-DD:YYYY-MM-DD. Max 7-day window per API call — skill paginates automatically.
group_by	—	workspace	Primary dimension: workspace, rep, or status.

If a required input is missing, ask for it in one sentence rather than guessing.

Process

Step 1 — Build the date range chunks

Parse date_range and split into 7-day (or shorter) chunks. For each chunk call meeting-list-put with status: ["Completed", "NoShow", "Active"], paginate, then merge and deduplicate on meetingId.

Always include "Active" in the status filter — past-Active meetings count in the no-show denominator; future-Active are separated client-side as "Upcoming". Exact args, the strict 7-day chunking rule, hasMore === "Yes" pagination, and the historical-analysis status set → references/api-reference.md § meeting-list-put — pagination and chunking and § Hard API limits.

Step 2 — Resolve workspaces (if group_by=workspace)

Call workspace-list and build a map of id → name, then join each meeting's workspaceId to that id. Exact args and the id-vs-workspaceId gotcha → references/api-reference.md § workspace-list — resolving workspace names.

Step 3 — Calculate org-wide metrics

Across all meetings, classify by meetingStatus. Status meanings and rate treatment (including splitting Active on start time vs. now) → references/api-reference.md § Meeting status values.

• Org no-show rate: NoShow / (Completed + NoShow + past-Active)
• Completion rate: (Completed + past-Active) / (Completed + NoShow + past-Active)

Surface a caveat when past-Active is a significant share of total (exact wording → references/output-format.md § Caveat line).

Step 4 — Calculate dimension breakdown

Group by the selected dimension and compute per-group metrics. Group key and name source per dimension → references/api-reference.md § Grouping fields by dimension.

• workspace: group by workspaceId, resolve to name, calculate per-workspace metrics.
• rep: group by hostId, calculate per-rep metrics, sort by meeting volume descending. Names are already present as hostName/hostEmail — no separate lookup.
• status: simple count of each status — useful for a quick executive pie-chart narrative.

For each group with ≥ 10 meetings, calculate no-show rate. Flag any group where rate > (org average + 10pp) or > 35%.

Step 5 — Output

Exact layout → references/output-format.md § Template. Suggested follow-up skills → references/output-format.md § Suggested follow-up skills.

Preflight audit

Verify before writing output. Every line must be a clear pass/fail:

• date_range parsed and split into chunks each strictly < 7 days.
• Field names and the status filter taken from references/api-reference.md, not guessed.
• "Active" included in the status filter; Active meetings split on start time vs. now (past-Active in denominator, not numerator).
• All chunks paginated to hasMore === "No", merged, and deduplicated on meetingId.
• Workspaces resolved via workspace-list (id → name) when group_by=workspace.
• Past-Active caveat surfaced when it is a significant share of total.

Checkpoint

Read-only skill: present the org summary, breakdown, and flags, then stop for the human:

"Should I send this to the summary view, or drill into any of the flagged groups?"

Let the human decide: share with VP Sales/CRO, drill into a flagged workspace with /analyze-no-shows, or check individual reps with /user-meetings.

Data handling

• PII present: rep emails used for grouping; surfaced in group_by=rep breakdown
• Storage: ephemeral — nothing persists after the skill completes
• Writes: none — read-only