Negotiation Pipeline Check

Negotiation Pipeline Check

Sweeps a deal export for deals sitting in negotiation with no mechanical path to a signature — no paper started, no approver on a discount, no credible close date, no mutual close plan, no named signer. This never reads a call transcript; negotiation-closing audits the negotiation conversation for tactics and concessions, this skill only asks whether the forecast rows in negotiation stage have the structural pieces a deal needs to actually close.

When to use this

• RevOps or a manager reviewing the negotiation-stage forecast for deals

that are "verbally close" but have no paper, approver, or close-date discipline behind them.

• A rep or manager sanity-checking their own negotiation-stage deals before

a forecast call.

• Spotting discount requests moving without an approver before they reach

legal/finance.

Step 1: Choose an input source

CSV mode (default) — read the .csv file the user points at directly.

Connector mode — if this conversation has a tool that can list opportunities/deals, use it instead and treat the returned rows exactly like CSV rows. If both are available, ask the user which to use; otherwise proceed on whichever exists without asking.

There is no transcript mode in this skill.

Step 2: Column detection

Match headers case-insensitively, ignoring _/-/space differences. Accept the synonyms listed in references/rubric.md. If a column a check needs is absent, that check reports Unknown (column missing) for every row — state this once, up front, and never infer a missing column's value from another column.

Step 3: Filter to negotiation stage

Keep rows whose stage column fuzzy-matches "negotiation" (e.g. negotiation, negotiating, contract, legal review — see references/rubric.md for the exact match list). Report how many rows were in scope out of the export's total row count.

Step 4: Run the six checks

Score every in-scope row against the six checks in references/rubric.md. Each check returns Flagged, Clean, or Unknown. Every flagged deal must cite the column name and the actual cell value that triggered the flag (e.g. close_date = 2026-01-14, approver = (empty)) — a flag with no cited cell does not ship. Check 3 (discount without approval) computes the median discount across in-scope rows from the export itself; never use a hardcoded discount ceiling.

Run the reads-well-too check from references/rubric.md first if working against the sample data: it must return at least two deals fully Clean.

Step 5: Output

One markdown table, flagged deals first, most flags first:

| Deal | Flags | Evidence | Suggested action | |---|---|---|---|

Then two closing lines:

• N of M deals in negotiation flagged
• The single most common flag across the flagged deals.

Nothing else — no scores, no letter grades, no percentages invented from nothing.

Run this end to end in one pass. Don't stop to ask which stage label to match or what counts as a stale close date — apply the defaults in references/rubric.md, decide, and note the assumption once.

Sample data

assets/sample-pipeline-negotiation-pipeline-check.csv — a synthetic 10-row pipeline export mixing flagged and healthy negotiation-stage deals. Run the skill against it first:

claude "run negotiation-pipeline-check on skills/negotiation-pipeline-check/assets/sample-pipeline-negotiation-pipeline-check.csv"

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 (or what a connector already present in the conversation returns) 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.