/patent-novelty-check

name: patent-novelty-check
description: "Assess patent novelty and non-obviousness against prior art. Use when user says \"专利查新\", \"patent novelty\", \"可专利性评估\", \"patentability check\", or wants to evaluate if an invention is patentable."
argument-hint: "[invention-description-or-brief-path]"
allowed-tools: Bash(*), Read, Write, Edit, Grep, Glob, WebSearch, WebFetch, mcp__codex__codex, mcp__antigravity__antigravity, mcp__antigravity__antigravity-reply, mcp__grok__grok, mcp__grok__grok-reply, mcp__claude-review__review, mcp__claude-review__review_reply, mcp__claude-review__review_start, mcp__claude-review__review_reply_start, mcp__claude-review__review_status

Patent Novelty and Non-Obviousness Check

> **Before each reviewer slot**, follow [Selectable Reviewers](../shared-references/reviewer-backends.md): > resolve invocation → `.aris/reviewer.json` → Claude Code default (Codex MCP) > with `reviewer_route.py` through the canonical helper resolver, preserving this > slot's tier, fresh contexts, source/image inputs and deterministic gates. > Codex examples/pins below apply only to `backend=codex`; other routes use their > own first-call/reply contract. Save the route and actual returned identity; > unavailable selections are `REVIEW_UNAVAILABLE`. Classify acceptance from actual > families/completion/scope. Forward invocation reviewer/model/effort overrides > to reviewer-bearing children. Generation workers are unchanged.

Assess patentability of: **$ARGUMENTS**

Adapted from `/novelty-check` for patent legal standards. Research novelty is NOT the same as patent novelty.

Constants

• `REVIEWER_MODEL = gpt-6-astra` — Model used via Codex MCP for cross-model examiner verification
• `NOVELTY_STANDARD = patent` — Always use legal patentability standard, not research contribution standard

Inputs

1. Invention description from `$ARGUMENTS` 2. `patent/PRIOR_ART_REPORT.md` (output of `/prior-art-search`) 3. `patent/INVENTION_BRIEF.md` if exists

Shared References

Load `../shared-references/patent-writing-principles.md` for novelty/non-obviousness standards. Load `../shared-references/patent-format-us.md` for 102/103 analysis framework.

Workflow

Step 1: Define Claim Elements

From the invention description, extract the key claim elements that would define the invention's scope: 1. List the technical features that make the invention novel 2. Identify which features are known from prior art vs. inventive 3. Draft preliminary claim language for 2-3 independent claims (method + system)

Step 2: Anticipation Analysis (Novelty)

For each preliminary claim, test against EACH prior art reference in `PRIOR_ART_REPORT.md`:

**Single-reference test**: Does any single reference disclose ALL claim elements?

| Claim Element | Ref 1 | Ref 2 | Ref 3 | ... | |--------------|-------|-------|-------|-----| | Feature A | Yes/No + evidence | | | | | Feature B | Yes/No + evidence | | | | | Feature C | Yes/No + evidence | | | | | Feature D | Yes/No + evidence | | | |

**Verdict per reference**:

• ANTICIPATED: One reference discloses every element → claim is not novel
• NOT ANTICIPATED: At least one element missing from every single reference → claim is novel

Step 3: Obviousness Analysis (Inventive Step)

If the invention is novel (passes Step 2), test for obviousness:

**Two/three-reference combination test**: Can 2-3 references be combined to render the claim obvious?

For each combination of the top references: 1. **Primary reference**: Which reference is closest to the claimed invention? 2. **Secondary reference(s)**: Which reference(s) teach the missing element(s)? 3. **Motivation to combine**: Would a POSITA have reason to combine these references?

• Explicit suggestion in the references themselves?
• Same field, same problem?
• Common design incentive?
• Known technique for improving similar devices?

Format as a matrix:

| Combination | Primary | Secondary | Missing Elements | Motivation to Combine | Obvious? | |-------------|---------|-----------|-----------------|----------------------|----------| | Ref1 + Ref2 | Ref1 | Ref2 | Feature D | Same field, similar problem | Yes/No |

Step 4: Cross-Model Examiner Verification

Call `REVIEWER_MODEL` via `mcp__codex__codex` with xhigh reasoning:

> Resolve this reviewer slot first; the following is the `backend=codex` example.

mcp__codex__codex:
  model: gpt-6-astra
  config: {"model_reasoning_effort": "xhigh"}
  prompt: |
    You are a senior patent examiner at the [USPTO/CNIPA/EPO].
    Examine the following invention for patentability.

    INVENTION: [invention description + preliminary claims]

    PRIOR ART: [prior art references with key teachings]

    Please analyze:
    1. Anticipation (novelty): Does any single reference anticipate any claim?
    2. Obviousness: Can any combination of references render claims obvious?
    3. Claim scope: Are the claims broad enough to be valuable?
    4. Recommended amendments if any claim is rejected.
    Be rigorous and cite specific references.

Step 5: Jurisdiction-Specific Assessment

For each target jurisdiction, provide a patentability assessment:

**Under 35 USC 102/103 (US)**:

• Novelty: PASS / FAIL (cite specific reference if fail)
• Non-obviousness: PASS / FAIL (cite combination if fail)

**Under Article 22 CN Patent Law (CN)**:

• 新颖性 (Novelty): 通过 / 未通过
• 创造性 (Inventive Step): 通过 / 未通过

**Under Article 54/56 EPC (EP)**:

• Novelty: PASS / FAIL
• Inventive step: PASS / FAIL (problem-solution approach)

Step 6: Output

Write `patent/NOVELTY_ASSESSMENT.md`:

## Patentability Assessment

### Invention Summary
[description]

### Overall Assessment
[PATENTABLE / PATENTABLE WITH AMENDMENTS / NOT PATENTABLE]

### Anticipation Analysis
[claim-by-claim matrix against each reference]

### Obviousness Analysis
[combination analysis with motivation to combine]

### Cross-Model Examiner Review
[summary of GPT-6-Astra examiner feedback]

### Re