How to Use Claude Opus 5 for Document Review Workflows
Reviewing a long document is not the same as summarising it. You need to catch what changed, flag what is missing, and cite where each finding came from. Claude Opus 5 handles this well when you structure the task around comparison rather than description.
The workflow below is built for contracts, policy documents, and technical specs. It assumes you have API or paid web access.
Why not just ask for a summary?
Because a summary tells you what the document says, and review is about what it fails to say and how it differs from the last version. Those are different tasks. Summaries also strip the clause references you need to verify anything.
Review output should always include a location. A finding without a section reference is an opinion.
How do you set up a review pass?
- Provide the current document with its structure intact, including section numbers.
- Provide the previous version if you are tracking changes.
- Give a checklist of what to look for — the model follows an explicit list far better than a general instruction.
- Require a citation for every finding: section number and quoted phrase.
- Ask for a confidence level per finding and review the low-confidence ones by hand.
Two documents in one context is the sweet spot. Compare three or more and the model starts blending them.
How do you write the checklist?
Be specific and exhaustive. “Check for issues” gets you vague notes. “Flag any clause that names a liability cap, any auto-renewal term, and any clause referring to undefined terms” gets you a list you can act on.
Useful checklist categories for contract work:
- Terms used but never defined.
- Obligations with no deadline or owner.
- Numbers that contradict each other elsewhere in the document.
- Clauses absent compared to your standard template.
The last category is the most valuable and the easiest to miss. Ask explicitly what a standard version of this document would include that this one does not.
How do you keep it honest?
Instruct it to quote the exact text for each finding. Quoting forces grounding — the model cannot invent a clause and attribute a quote to it without visibly fabricating.
Then spot-check. Open three findings at random and confirm the quoted text exists at the cited section. If the quotes hold, the rest of the output is usually trustworthy. If they do not, stop and fix the prompt before reading further.
Ask it also to say “not found” rather than omitting a category. Silence in the output is ambiguous; an explicit “not found” tells you the checklist item was actually checked.
What are the limits?
It is not a lawyer and it does not understand jurisdiction-specific law. It will not catch a clause that is legally unenforceable but perfectly drafted. Use it to produce a faster first pass, then have a qualified person review the flagged items.
Confidentiality is the other consideration. Sending contracts to a hosted API means the text leaves your network. For sensitive documents, confirm your data handling terms or use a self-hosted option instead.
Does the API make sense here?
Yes if review is a recurring part of your work. A script that submits a document with a fixed checklist returns consistent output and builds an audit trail. If you review one document a month, the web interface is simpler.
Quick Summary
- Treat review as comparison, not summarisation — always require locations.
- Feed two documents at most: the current one and the prior version.
- Give an explicit checklist; ask what a standard document would include.
- Require direct quotes for each finding, then spot-check three.
- It is a first pass, not legal advice — get human review on flags.
