— Legal & Contracts

Contract metadata extraction at scale

Enriches every row of a contracts export with parties, value, term, renewal basis and governing law, turning a messy list into a queryable contract database with the outliers named.

  • Legal & Contracts
  • Traceable reasoning
  • Runs anywhere
Preview methodology

1–2 weeks → ~15 minutes

For a full population, not a sample

No coding required

Input
Contract registers and portfolio lists
Output
Enriched, queryable contract database
Runs in
Skillsize · ChatGPT · Claude · Copilot
Export
SKILL.md · MCP
Time saved
~1–2 weeks per run

— USE CASES

What people use Contract metadata extraction at scale for

Contract portfolio due diligence

Provides a structured view of parties, values, terms and legal jurisdictions across a large contract portfolio. A summary of outliers helps advisers focus legal review where it matters.

Renewal exposure assessment

Makes contract terms and renewal bases comparable across inconsistent records, supporting assessment of ongoing commitments and renewal exposure.

Cross-border portfolio review

Groups contracts by governing law and captures jurisdiction details, giving legal teams a clearer picture of the portfolio's legal coverage.

Unusual clause review

Flags unusual provisions in the available contract text and identifies outliers in a summary report, giving lawyers a focused basis for further assessment.

What it works from

  • Contract registers and portfolio lists
  • Contract titles and descriptive summaries
  • Clause text and contract extracts
  • Existing commercial and legal contract metadata

What you get back

  • Enriched, queryable contract database
  • Contract party details
  • Contract values and currencies
  • Contract terms and renewal bases documentation removed

— HOW IT BEHAVES

How Contract metadata extraction at scale produces its result

The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.

Every row of the contract portfolio

Each row of your export is processed on the same basis, so no clause is skipped however long the table is.

Composed as work product

Findings on the contract portfolio are written up as a document that reads like professional output, with each claim tied back to a clause.

Each clause enriched in place

Derived columns are added row by row, keeping your source data and the judgement about each clause side by side.

Roll-up alongside clause-level detail

Detail rows are summarised into the grouped view of the contract portfolio without losing the underlying clauses.

Why this is expensive by hand

Contract portfolios often contain uneven descriptions, partial clause extracts and inconsistent records, making it difficult to compare exposure or identify agreements that deserve closer attention. Contract portfolio due diligence is the typical trigger — provides a structured view of parties, values, terms and legal jurisdictions across a large contract portfolio. A summary of outliers helps advisers focus legal review where it matters. Get it right and the conclusion holds up in the room; get it rushed and it gets picked apart. Either way it costs roughly 1–2 weeks of experienced attention.

How this Skill produces it

As a Skill, the work is already sequenced. You bring the evidence, and the run produces enriched, queryable contract database plus contract party details. The judgement is built in — how items are broken up, what standard they are held to, and where the run stops for a human review. Net effect: 1–2 weeks down to ~15 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.

Who it's for

  • In-house legal and contract managers
  • Commercial and procurement leads reviewing terms
  • Operations teams handling contract volume
  • Consultants advising on contractual risk

Run it in Skillsize — or export it anywhere

Contract metadata extraction at scale exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.

ChatGPTClaudeCopilotAI Products (MCP)