Install
$ agentstack add skill-zime-ai-zime-gtm-skills-won-pipeline-check ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Won Pipeline Check
Sweeps a deal export for closed-won deals missing the data the next team needs to run the handoff. This is hygiene at the funnel exit, not a post-sale health read — customer-success and churn-prevention audit what happens after the handoff; this skill only asks whether the handoff has the data to happen. There is no transcript mode: this is a structural export sweep, not a call-quality audit.
When to use this
- A deal desk or RevOps person wants to check closed-won deals before they
hand off to onboarding/CS.
- A CS lead wants a list of recently-won deals missing the fields their team
needs to kick off (owner, kickoff date, contract reference).
- Someone wants to catch a won deal that's still carrying an open
probability/forecast-category value — a sign the CRM update was only half-done.
How to run it
claude "run won-pipeline-check on ./exports/pipeline.csv"
Input. A .csv deal/pipeline export. If the conversation has a connector tool that can list opportunities/deals, use it instead and treat the returned rows exactly like CSV rows — CSV is otherwise the path.
Column detection. Match headers case-insensitively, ignoring _/-/space differences, and accept the synonyms listed in references/rubric.md. If a column a check needs is absent from the export, that check reports Unknown (column missing) for every row — state this once, up front, and never infer the value from another column.
Stage filter. Operate only on rows whose stage fuzzy-matches "Won pipeline" (i.e. Closed Won and close synonyms — see references/rubric.md). Report how many rows were in scope and how many the export held in total.
Run each of the six checks in references/rubric.md against every in-scope row. Each check returns Flagged, Clean, or Unknown.
Evidence rule. Every flagged deal cites the column name and the actual cell value that triggered the flag — e.g. close_date = 2026-01-14, or champion = (empty). A flag with no cited cell does not ship.
Reads-well-too check. Apply the check in references/rubric.md before finalizing — a rubric that flags everything is useless.
Output
One markdown table, flagged deals first, most flags first:
| Deal | Flags | Evidence | Suggested action |
Then two closing lines:
N of M deals in Won pipeline flagged- The single most common flag across them.
Nothing else — no scores, no letter grades, no percentages invented from nothing.
Sample data
assets/sample-pipeline-won-pipeline-check.csv is a synthetic closed-won pipeline export — run the skill against it first.
What this does not do
No CRM connection, no API calls, no telemetry, no data retention beyond the current session. It reads the file(s) you point it at and nothing else.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: zime-ai
- Source: zime-ai/zime-gtm-skills
- License: MIT
- Homepage: https://zime.ai
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.