Pipeline Review

Instructions

Setup state. Not yet configured for this org. Load the Setup sub-page and walk the user through mapping their CRM stages to the Swan funnel model, recording per-stage SLAs, and setting the review cadence before running a review. (After setup is performed, rewrite this paragraph via swan-update-skill to describe the current state — funnel stages mapped from CRM, required field mappings, per-stage SLAs in days, review cadence and delivery channel, and last-refreshed date — so future runs see the current configuration without re-checking.)

What this skill does

Walk the user's pipeline. Surface deals that need attention: stalled in stage, regressed in stage, missing key activities, or showing risk signals. Output: a short prioritized list with one action per item. Not a forecast — that's a separate verb.

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Step 1 — Scope the review

Ask once:

• Whose pipeline (a specific AE, a team, the whole org)?
• Which stages (mid-funnel only by default — exclude early discovery and closed)?
• Time horizon (default: deals expected to close this quarter, plus anything aging > 30 days regardless of close date).

If the user hasn't said which AE, default to all open mid-funnel deals.

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Step 2 — Pull the deal slice

hubspot-search-objects (object: deals) filtered to the chosen owner(s), open stages, and the date window. Page size 20. Pull associated company and amount.

If the result is > 40 deals, switch to swan-execute-code: dump the deals query result and aggregate from disk.

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Step 3 — Flag anomalies per deal

For each deal in the slice, check three things (cheap, no enrichment):

| Flag | Check | How | |------|-------|-----| | Stalled | No engagement / activity update > 21 days | Deal hs_lastmodifieddate > 21 days ago | | Regressed | Stage went backwards | Check stage history if available; or compare to prior pipeline snapshot in memory | | Risk: low engagement | 90 days out for a "this quarter" deal | Compare to today |

Keep one line per flagged deal: — — . Discard the rest.

If a deal has multiple flags, list them comma-separated on the same line.

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Step 4 — Pull fresh signals for at-risk deals only

For each flagged deal, check one source: swan-fetch-business-events on the associated company in the last 30 days. If a fresh signal exists, note it — it's the angle to act on.

Skip signal lookup for unflagged deals. Most pipeline reviews are about the at-risk subset.

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Step 5 — Recommend one action per flag

Lightest first:

| Flag | Default action | Tool | |------|----------------|------| | Stalled, fresh signal exists | Draft a signal-based re-engagement | hand off to reach-out | | Stalled, no fresh signal | Create a CRM task for the owner to call/email manually | hubspot-create-task + hubspot-create-note | | Regressed | Create a task to schedule a deal review with the owner | hubspot-create-task | | Low engagement | Hand off to multi-thread-deals to identify missing personas | multi-thread-deals | | Champion gone | Hand off to champion-tracker to find the champion's new role | champion-tracker | | Amount missing / close date stale | Create a task for the owner to update the deal | hubspot-create-task |

Don't auto-execute. List the recommendation. Ask which to proceed with.

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Step 6 — Surface the report

PIPELINE REVIEW — , 

 deals reviewed.  flagged.

STALLED (X)
  1.  —  — last activity Y days ago — fresh signal: 
     → 

REGRESSED (X)
  ...

RISKS (X)
  ...

End with a bottom line: "X actions recommended. Want me to create the CRM tasks for the top N?" Wait for approval before writing anything to CRM.

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Rules

• MUST process deals in slices of 20. Don't load the whole pipeline into context.
• MUST cite specific evidence per flag (days, dates, counts).
• MUST end with an explicit approval gate before creating CRM tasks.
• NEVER recommend more than 10-15 actions in a single review. Bigger lists won't get acted on. If more deals are flagged, surface top 10 and offer to do the rest in a follow-up pass.
• NEVER flag deals as stalled if they're in a stage where 21 days is normal (custom stages — confirm the org's stage SLAs from memory before flagging).

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: swan-gtm
• Source: swan-gtm/gtm-skills
• License: MIT

Install and usage instructions live in the source repository linked above.