/lynqu-pipeline-report

name: lynqu-pipeline-report
description: Weekly Lynqu pipeline and sales report — what moved, what's stalling, campaign and event ROI, card engagement, who needs attention. Read-only. Requires the Lynqu MCP server connected.

Lynqu Pipeline Report

You produce the briefing a sales leader reads on Monday morning: what moved, what didn't, what's at risk, and the three things to do about it. **This skill is read-only.** It never writes, never sends, never moves a stage. That constraint is what makes it safe to run on anything, and it's why it's the natural last step after every other skill in the suite.

A report that lists numbers is a dashboard, and the user already has one. A report that says *"the pipeline looks healthy but 60% of it is one deal that hasn't moved in five weeks"* is worth the read.

Invocation

/lynqu report [week | month | quarter | board | rep | campaign | event]

Defaults to the last 7 days across the whole org, scoped to what the caller's role can see.

Step 1: Gather

Pull broad first, then drill only where something looks wrong.

| Source | What it gives you | |--------|-------------------| | `get-org-summary` | The shape: counts by stage, activity, campaigns | | `get-dashboard-summary` | Headline numbers, pre-aggregated | | `list-leads` (by stage, updated window) | Movement and staleness — the raw material | | `get-forecast` | Weighted pipeline by forecast category (manager+) | | `list-campaigns` + `get-campaign` | Spend against return | | `get-event-portfolio` | Cross-event roll-up: leads, pipeline, won, cost | | `list-events` | What's live and what's closing | | `get-team-performance` / `get-employee-performance` | Per-rep (add-on gated) | | `get-card-stats` / `list-org-cards` | Card engagement — the top of the funnel | | `list-dashboards` + `get-dashboard-data` | The org's own saved widgets (analytics add-on) | | `list-lead-duplicates` | Data quality that's distorting every number above |

Skip cleanly on `ADDON_REQUIRED`. Analytics dashboards and team performance are add-ons; the core report needs neither. Mention the omission once, at the end, without turning it into an upsell.

Step 2: Analyse — differences, not totals

A total is a fact. A difference is information.

1. **Movement.** What entered, advanced, was won, was lost. Compare with the previous equivalent period. "12 new leads" means nothing; "12 new, against a 4-week average of 31" is the headline. 2. **Concentration.** How much of the pipeline is one deal, one rep, one campaign? This is the risk nobody puts on a dashboard, and it's usually the real story. 3. **Stalls.** Leads past 2× the median time in stage, and where they pile up. A specific stage that always clogs is a process problem, not a rep problem. 4. **Velocity.** Time from creation to won, and whether it's changing. 5. **Conversion by stage.** Where deals actually die. If half of Evaluation goes to lost, the problem started earlier, in qualification. 6. **Source quality.** Win rate by capture source and campaign. Volume flatters the wrong channel constantly. 7. **Coverage.** Weighted pipeline against target. Say the ratio plainly. 8. **Hygiene.** Duplicates, orphaned leads, open leads with no next step. These are the caveats every other number in the report needs.

Step 3: Turn analysis into recommendations

Every finding needs a **so what**. Three to five recommendations, ranked by impact, each naming a specific action, a specific target, and who does it.

Bad: "Follow-up could be improved." Good: "9 hot leads from SaaStr have had no touch in 6 days — the 48-hour window is gone. Run `/lynqu followup` on that cohort today; expected recovery is 2–3 meetings based on the last event's rate."

Rank by revenue impact, not by how easy the fix is.

Step 4: Say what you can't see

Every report states its own limits. This is not a disclaimer, it's the part that makes the rest trustworthy:

• Which surfaces were unavailable (add-ons, role scope)
• Data quality problems that distort the numbers — duplicates double-count value,

leads with no value set are invisible in the forecast

• Where the sample is too small for the percentage to mean anything. "3 of 4 = 75%

win rate" is not a win rate

A leader who catches a report overstating its confidence once will discount every report after it.

Output format

# Pipeline Report — {period}

**{One-sentence verdict.}**

## The number
| | This period | Previous | Δ |
|---|---|---|---|
| New leads / Advanced / Won / Lost / Pipeline value / Weighted forecast | … | … | … |

## What moved
{3–5 bullets. Named deals, real numbers.}

## What's at risk
| Risk | Evidence | Impact |
|------|----------|--------|
| Concentration | 62% of pipeline is one deal, static 5 weeks | Forecast is one conversation |

## By source
| Source | Leads | Won | Win rate | Note |

## By rep
| Rep | Open | Advanced | Won | Stalled |

## Events & campaigns
| Name | Spend | Leads | Qualified | Pipeline | Cost/qualified |

## Do this week
1. {Action} — {who} — {expected impact}

## Caveats
{Unavailable surfaces · data quality · small samples.}

Keep the top of the report to what fits on a phone screen. Depth goes below.

Rules and constraints

• **Read-only. Always.** No stage moves, no sends, no tags, no "while I was in

there". If the report surfaces work, hand it to the skill that owns it.

• **Never state a number you didn't read.** No extrapolation presented as fact.
• **Always compare to a baseline.** A number with no comparison isn't a finding.
• **Flag small samples.** Percentages on fewer than ~10 records get labelled.
• **Respect role scope.** An employee's report covers their own leads; a manager's

covers their departments. Say which scope you used, so nobody mistakes a partial view for the whole company.

• **Lead with the problem**, not with the total. Leaders skim.
• **Never dress a bad period up.** "Down 40% on a 4-week average" is the sentence