| name | business-pulse |
| description | Live firm-wide sales pulse from the Epiphan CRM — revenue vs pace, pipeline by stage, won/lost, BDR activity, with coaching takeaways. Use when: business pulse, how are we doing, pipeline health, revenue pace, weekly numbers, standup brief, are we on track, sales snapshot. |
Give a new SDR (or a manager in standup) a live, honest read on the business in one shot: are we on
pace, where's the pipeline, what won/lost, how's BDR activity — then three "so-what" takeaways. Pulls
REAL data from the Epiphan AI MCP every run. Tool reference: see `epiphan-ai-mcp-guide-skill`.
<quick_start>
Trigger: "business pulse", "how are we doing", "weekly numbers", "standup brief".
One call gets you 90% of it:
weekly_brief({})
Then synthesize into the Output shape below (never dump raw JSON). For the new SDR cohort or deeper
cuts, use the query_dataset calls in "How to run it". Reference material: reference/ in this skill
epiphan-ai-mcp-guide-skill (golden defaults, owner IDs, verticals pack).
</quick_start>
How to run it
-
One-shot brief (start here):
weekly_brief({})
Returns revenue (week/MTD/QTD/YTD + prior-year), deals won/lost, new contacts by lifecycle +
source, BDR activity, and AE pipeline by stage — already tuned to FY2026 (start 2025-11-01),
$19.5M target, BDR IDs 87486452 (Tim) / 423155215 (Ron).
Track the new SDR cohort (Edgar / Vasil / Nyasha — onboarded June 2026) explicitly:
weekly_brief({ bdr_owner_ids: ["93367782","93782443","94135434"] })
query_dataset({ dataset: "rep_activity", group_by: ["owner"],
filters: { owner_ids: ["93367782","93782443","94135434"] } })
(IDs + Nooks mapping live in epiphan-ai-mcp-guide-skill golden defaults.)
-
Deeper cuts as needed:
query_dataset({ dataset: "pipeline_open", group_by: ["owner","stage"] })
query_dataset({ dataset: "revenue", group_by: ["period_month"], date_from: "2025-11-01", date_to: "2026-11-01" })
query_dataset({ dataset: "deals_closed", group_by: ["outcome"], date_from: <quarter start>, date_to: <quarter end> })
-
Synthesize into the output shape below — never just dump JSON.
Output shape
BUSINESS PULSE — week ending <date>
PACE YTD $<x> of $19.5M target → <n>% of FY pace [On / Behind / Ahead]
REVENUE Week $<x> · MTD $<x> · QTD $<x> · YoY <±%>
PIPELINE $<x> open across <n> deals
by stage: Discovery $<x> · … · Commit $<x>
WON / LOST Won <n> ($<x>) · Lost <n> ($<x>) this period
BDR Tim: <dials/connects/meetings> · Ron: <…>
TOP MOVERS <2-3 notable deals advancing or slipping>
SO WHAT (coaching)
1. <where the gap is, and the single highest-leverage action>
2. <a stage with stalled volume → who multi-threads it>
3. <a vertical/segment signal worth a play this week>
Vertical-awareness — and its honest limit
There is no native vertical/industry dimension in the datasets (group_by =
period/owner/stage/outcome/country/pipeline/lifecycle/source). So any HigherEd / Community College
/ Live Events / Corporate / Broadcast split is derived — proxy via source/pipeline/country,
or enrich the top open deals account-by-account (sales_brief). Always label a vertical breakdown as
approximate; never present a fabricated clean split. (Vertical pack: epiphan-ai-mcp-guide-skill/reference/verticals.md.)
Coaching lens (tie back to the data we have)
- Every 2026 loss was single-threaded below Manager level → if a big deal sits in Discovery, the play
is "thread up to the economic buyer," not "follow up."
- 22 of 29 HigherEd deals stalled in Discovery → Discovery-stage bulk is the leading indicator to act on.
Guardrail — internal only
Output is internal. Naming partners/competitors here is fine; anything buyer-facing must stay clean
(no AV-matrix mechanism, no third-party brand names — "your CMS / LMS"). The pooled figure is "a more
affordable path, a starting point, not a quote." See epiphan-ai-mcp-guide-skill.
<success_criteria>
