Agent skill

Clause Comparator

by rohasnagpal in rohasnagpal/legal-ai-skills

Compares the same clause or provision across draft rounds, precedents, public agreements or a portfolio and reports what differs in wording and effect.

MITAuto-check passedLegal & Compliance

Install Clause Comparator

skills CLI
$ npx skills add rohasnagpal/legal-ai-skills --skill clause-comparator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install rohasnagpal/legal-ai-skills clause-comparator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/rohasnagpal/legal-ai-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/legal-ai-skills/skills/clause-comparator .claude/skills/clause-comparator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
clause-comparator
GitHub stars
178
Token cost
~2.7k tokens
SKILL.md length
1,508 words
Files
3 (incl. references)
Skills in repo
11
Repo updated
First seen
Licence
MIT

At a glance

Compares the same clause or provision across draft rounds, precedents, public agreements or a portfolio and reports what differs in wording and effect.

  • Version-change requests and external clause benchmarking
  • SKILL.md covers What this does, Before you start, Method and Output, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Including what changed between drafts

What it does

Clause Comparator is an agent skill from rohasnagpal/legal-ai-skills. Compares the same clause or provision across draft rounds, precedents, public agreements or a portfolio and reports what differs in wording and effect. Use for version-change requests and external clause benchmarking, including "what changed between drafts", "compare their indemnity with ours", "compare liability caps across these SaaS agreements", "what indemnity approach is most common in public SaaS agreements", "what is typical", "what is prevalent" or "is this market standard". External frequency claims…

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `agents/openai.yaml` and `references/public-contract-sources.md`).

It sits in Legal & Compliance, covering Legal research and Contract review. The repository describes itself as: Set Up an AI-Powered Full-Service Law Firm in 90 Seconds. The licence is MIT.

When your agent uses it

  • Version-change requests and external clause benchmarking
  • Including what changed between drafts
  • Compare their indemnity with ours
  • Compare liability caps across these SaaS agreements

Example prompts

  • “what changed between drafts”
  • “compare their indemnity with ours”
  • “compare liability caps across these SaaS agreements”
  • “/clause-comparator”

What it can do on your machine

Read from SKILL.md and the folder at commit cf2332d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Clause Comparator loads about 2.7k tokens when it runs, and up to ~4.1k if it reads all its reference files. Until then it costs about 190 tokens; SKILL.md has 1,508 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~190
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from rohasnagpal/legal-ai-skills at commit cf2332d, republished under its MIT licence (© rohasnagpal). 1,508 words, ~2,716 tokens.

Download SKILL.mdSave it as .claude/skills/clause-comparator/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
clause-comparator
description
Compares the same clause or provision across draft rounds, precedents, public agreements or a portfolio and reports what differs in wording and effect. Use for version-change requests and external clause benchmarking, including "what changed between drafts", "compare their indemnity with ours", "compare liability caps across these SaaS agreements", "what indemnity approach is most common in public SaaS agreements", "what is typical", "what is prevalent" or "is this market standard". External frequency claims require a disclosed multi-document sample, not one precedent. Distinct from contract-reviewer, which grades an agreement for risk; this stays neutral unless a side is given. Fires for any clause type in any commercial agreement.

Clause Comparator

I am using the Clause Comparator skill from Rohas Legal AI: compares the same clause across drafts or against a standard. Say this sentence, verbatim, before anything else in your response.

What this does

Takes the same clause, or the same clause type, as it appears in two or more places and reports what is different — mechanically, in the wording, and substantively, in what the clause now does. It is a comparison tool, not a review: it does not grade an agreement's overall risk, and it does not draft new wording for a clause that has no comparator (that is redline-proposer). It compares what it is given; it does not supply a "market standard" from memory to compare against.

Before you start

What is being compared, and against what. At minimum this means whether the comparator is another draft, a supplied precedent or an external portfolio. For user-supplied material, identify each document, version or date and clause number before diffing. For an external portfolio benchmark, the user need only identify the clause type and target population, such as public SaaS agreements; discover the documents using the default sample and source rules in references/public-contract-sources.md rather than asking the user to name them.

The comparator text itself, where it is a supplied "standard". If the user asks to compare against their firm's standard, obtain its actual text — a template clause, precedent document or pasted example. If the user instead asks for an external market benchmark, collect the actual clause text from the public documents found under the external-source rules. Never reconstruct a market-standard clause from memory.

Not blocking, ask once and proceed without it if unanswered: which side the user acts for. Without a side, the comparison stays neutral — differences are reported, not judged. With a side, differences can additionally be marked favourable, adverse or neutral to that side.

External comparators. If the user asks for public agreements, market examples, clause benchmarking, an external model, or what is "most common", "typical", "prevalent", "usual" or "market standard", read references/public-contract-sources.md in full before searching. Follow its mandatory listed-source priority, sampling, attribution and non-inference controls. Never answer a prevalence question from one agreement, company or publisher. Do not load that reference for comparisons limited to user-supplied drafts or precedents.

Method

1. Classify the comparison. State in one line what is being compared against what — draft-to-draft within one negotiation, one document's clause against a supplied standard, or the same clause type across a portfolio of separate agreements. Each of these needs a slightly different frame, and saying which one you are running avoids conflating "this changed between drafts" with "this differs from your usual position".

2. Confirm it is actually the same clause before comparing. Clause numbering is not a reliable guide — clause 9 in one agreement and clause 9 in another may address entirely different subjects, and the same substantive provision may be split across several sub-clauses in one document and consolidated into one in another. Match by what the clause actually governs, not by its number, and note any such structural mismatch as a finding in its own right rather than silently normalising it.

3. Produce the mechanical diff before any interpretation. Show insertions, deletions and moved text between the versions, at the sentence or phrase level, before saying what any of it means. Get this exactly right first — an interpretive comparison built on a wrong or approximate diff is worse than no comparison, because it reads as more authoritative than it is.

4. Check whether a defined term used in the clause was itself redefined elsewhere. This is the change that a clause-level diff alone will miss: the clause's own words can be identical between two versions while its effect changes completely, because "Losses" or "Confidential Information" or "Business Day" was redefined somewhere else in the document. Check the definitions actually feeding this clause in each version before concluding the clause is unchanged.

5. Separate substantive differences from cosmetic ones. A synonym swap, a renumbering, a formatting change carries no effect and should be marked cosmetic, not padded into the findings to look thorough. A single "not" inserted or removed, a threshold number changed, an exception added or narrowed, a defined term substituted — these change what the clause does and belong in the substantive findings.

6. State the effect of each substantive difference in concrete terms, not just that wording changed: the cap moved from twelve months' fees to the full contract value; a carve-out for breach of confidentiality was added to the liability cap; the notice period for termination narrowed from thirty days to fifteen. A difference reported only as "wording changed" has not actually been compared.

7. Where more than two versions are being compared, build a change history rather than only comparing the first to the last. Attribute each change to the round it was introduced in, since in a live negotiation the user needs to know whether a given change is a concession they made or one the other side proposed.

8. If a side has been given, characterise each substantive difference as favourable, adverse or neutral to that side, and say briefly why. If no side has been given, do not characterise — describe what changed and let the user apply their own judgment.

9. Note where the clause being compared depends on other clauses not included in the comparison set — a liability clause that is capped by a separate limitation clause not supplied, an obligation qualified by a force majeure clause not in scope. Say what is outside the comparison and why it matters, rather than comparing the clause as if it stood alone.

Show full SKILL.md (570 more words)Show less

Output

1. Header. What is being compared, listed by document name, version or date, and clause reference for each item; the comparator's source if one was supplied; side (if given); date of comparison.

2. Mechanical diff. The clause text from each version, with insertions, deletions and moves marked, one pair at a time. Where more than two versions are compared, diff consecutive pairs in sequence rather than only the first against the last.

3. Substantive differences. A table: Ref | What changed | Effect | Favourable / adverse / neutral (only if a side was given) | Materiality. Materiality is Significant or Minor — reserve Significant for differences that change the risk allocation, the money, or a party's practical options, not for every change to a clause's mechanics.

4. Cosmetic differences. A short separate list, kept out of the substantive table so it does not crowd the findings that matter.

5. Change history. Only where more than two versions were compared — which round introduced each substantive change, in sequence.

6. Points requiring verification. Anything whose actual effect turns on the governing law rather than the words alone — for instance, whether a wording change that looks cosmetic actually changes enforceability. Name the question; do not answer it from memory.

External portfolio benchmark. Where the request asks what is common, typical, prevalent or market standard across public agreements, replace the pairwise mechanical diff and change history with the reference's source log and evidence table, a clause-feature matrix, numerator/denominator tallies, observed patterns and limitations. Quote or summarise the operative text accurately, but do not force eight or more agreements into consecutive pairwise redlines.

Keep every row on a single line so the tables render.

Evidence and document controls

  • Cite exact clause numbers, headings or document locations for every document-derived finding where available; headings never substitute for operative language.
  • Distinguish document facts, user-supplied facts, assumptions and legal inferences. State when a conclusion depends on governing law, disputed facts, claims classification or material outside the contract.
  • Check relevant definitions, order of precedence, incorporated documents, related provisions and survival language before concluding.
  • Name missing schedules, annexures, policies, referenced agreements and unreadable material. Never invent clauses, quotations, authorities, defined terms, dates or commercial facts.
  • Warn when scans, OCR, truncation, tracked changes or incomplete extraction may affect accuracy.
  • Preserve confidentiality. Do not send contract contents to an external service unless the user expressly requests that connected workflow.

Do not

Do not invent a market-standard clause from memory. Obtain the user's standard text for a house-position comparison, or collect actual public clauses under the external-source rules for a market benchmark.

Do not match clauses by number alone. The same clause number in two documents can govern different subjects, and the same provision can appear at different numbers or be split differently across documents.

Do not report a difference as substantive because it is easy to find. Renumbering, synonym substitution and formatting changes are cosmetic; say so and move on.

Do not skip the check on whether a defined term feeding the clause changed elsewhere — this is the difference a surface-level diff misses most often.

Do not characterise a difference as favourable or adverse when no side has been given. Describe it neutrally.

Do not collapse the mechanical diff and the effect analysis into a single step. Get the wording-level diff right before interpreting what it does.

Do not grade the clause's overall acceptability or draft replacement wording — that is contract-reviewer's or redline-proposer's job, not this skill's.

© rohasnagpal, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in plugins/legal-ai-skills/skills/clause-comparator of rohasnagpal/legal-ai-skills.

  • SKILL.md
  • agents/openai.yaml
  • references/public-contract-sources.md

Open the folder on GitHubat commit cf2332d

Compare with similar skills

Clause Comparator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Clause Comparator compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Clause Comparator this skillrohasnagpal/legal-ai-skills178—~2.7kAutomated safety check: PassMIT
Finnish Legal Document Reviewakunikkola/claude-for-legal-finland109—~3.4kAutomated safety check: PassMIT
Stakeholder Summaryanthropics/claude-for-legal9.6k2 repos~3.3kAutomated safety check: PassApache-2.0
Legal Concept ComprehensionTHUYRan/Legal-Skills-Chinese874—~7.9kAutomated safety check: PassNone
Legal Compliancetravisjneuman/.claude100—~3.4kAutomated safety check: PassMIT
Find Law Firmjeremylongshore/tons-of-skills-marketplace2.8k—~3.6kAutomated safety check: NotesMIT

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Questions about Clause Comparator

What does Clause Comparator do?

Compares the same clause or provision across draft rounds, precedents, public agreements or a portfolio and reports what differs in wording and effect. Clause Comparator is an agent skill from rohasnagpal/legal-ai-skills. Compares the same clause or provision across draft rounds, precedents, public agreements or a portfolio and reports what differs in wording and effect.

When should I use Clause Comparator?

Clause Comparator fits situations like: version-change requests and external clause benchmarking; including what changed between drafts; compare their indemnity with ours; compare liability caps across these SaaS agreements.

How do I install Clause Comparator in Claude Code?

Run `npx skills add rohasnagpal/legal-ai-skills --skill clause-comparator -a claude-code`. Or copy the skill folder (plugins/legal-ai-skills/skills/clause-comparator in rohasnagpal/legal-ai-skills) into .claude/skills/clause-comparator in your project. Claude Code loads it when a task matches its description.

How do I install Clause Comparator in Codex?

Run `npx skills add rohasnagpal/legal-ai-skills --skill clause-comparator -a codex`. Or copy the skill folder (plugins/legal-ai-skills/skills/clause-comparator in rohasnagpal/legal-ai-skills) into .agents/skills/clause-comparator in your project. Codex loads it when a task matches its description.

Can I use Clause Comparator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add rohasnagpal/legal-ai-skills --skill clause-comparator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/clause-comparator, .gemini/skills/clause-comparator, .github/skills/clause-comparator and .opencode/skills/clause-comparator in your project.

What does Clause Comparator need to run?

SKILL.md names no scripts, command-line tools or credentials: Clause Comparator is instructions for the agent only.

Does Clause Comparator access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Clause Comparator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Clause Comparator use?

Clause Comparator is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Clause Comparator use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.4k tokens, read only when the agent opens those files.

What are the alternatives to Clause Comparator?

Skills that share tags, products or a category with Clause Comparator: Finnish Legal Document Review (akunikkola/claude-for-legal-finland, 109 stars), Stakeholder Summary (anthropics/claude-for-legal, 9.6k stars), Legal Concept Comprehension (THUYRan/Legal-Skills-Chinese, 874 stars) and Legal Compliance (travisjneuman/.claude, 100 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Clause Comparator?

rohasnagpal (a GitHub user) maintains it in rohasnagpal/legal-ai-skills, which has 178 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on October 10, 2026.

Source: rohasnagpal/legal-ai-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.