drive-pr-local-review — for Claude Code drive-pr-local-review, prisma-next, community, for Claude Code, ide skills, loggy-core, loggy-terminal, spec.md, system-design-review.md, code-review.md

v2026.4.15.1

このスキルについて

適した場面: Ideal for AI agents that need a code review must be anchored to expectations . those expectations come from:. ローカライズされた概要: # Local PR Review Premise A code review must be anchored to expectations . It covers loggy-core, loggy-terminal workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

機能

A code review must be anchored to expectations . Those expectations come from:
Explicit intent sources (PR description, linked tickets, design docs) when available, plus
You do not change implementation code. You only write review artifacts.
Outputs (always written to disk)
Every run must produce these artifacts side-by-side :

# Core Topics

prisma prisma
[267]
[3]
Updated: 4/15/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 10/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
10/11
Quality Score
82
Canonical Locale
en
Detected Body Locale
en

適した場面: Ideal for AI agents that need a code review must be anchored to expectations . those expectations come from:. ローカライズされた概要: # Local PR Review Premise A code review must be anchored to expectations . It covers loggy-core, loggy-terminal workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

このスキルを使用する理由

推奨ポイント: drive-pr-local-review helps agents a code review must be anchored to expectations . those expectations come from:. Local PR Review Premise A code review must be anchored to expectations . This AI agent skill

おすすめ

適した場面: Ideal for AI agents that need a code review must be anchored to expectations . those expectations come from:.

実現可能なユースケース for drive-pr-local-review

ユースケース: Applying A code review must be anchored to expectations . Those expectations come from:
ユースケース: Applying Explicit intent sources (PR description, linked tickets, design docs) when available, plus
ユースケース: Applying You do not change implementation code. You only write review artifacts

! セキュリティと制限

  • 制約事項: A code review must be anchored to expectations . Those expectations come from:
  • 制約事項: You do not change implementation code. You only write review artifacts.
  • 制約事項: Every run must produce these artifacts side-by-side :

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

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FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is drive-pr-local-review?

適した場面: Ideal for AI agents that need a code review must be anchored to expectations . those expectations come from:. ローカライズされた概要: # Local PR Review Premise A code review must be anchored to expectations . It covers loggy-core, loggy-terminal workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

How do I install drive-pr-local-review?

Run the command: npx killer-skills add prisma/prisma-next/drive-pr-local-review. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for drive-pr-local-review?

Key use cases include: ユースケース: Applying A code review must be anchored to expectations . Those expectations come from:, ユースケース: Applying Explicit intent sources (PR description, linked tickets, design docs) when available, plus, ユースケース: Applying You do not change implementation code. You only write review artifacts.

Which IDEs are compatible with drive-pr-local-review?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for drive-pr-local-review?

制約事項: A code review must be anchored to expectations . Those expectations come from:. 制約事項: You do not change implementation code. You only write review artifacts.. 制約事項: Every run must produce these artifacts side-by-side :.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add prisma/prisma-next/drive-pr-local-review. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use drive-pr-local-review immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

drive-pr-local-review

# Local PR Review Premise A code review must be anchored to expectations . It covers loggy-core, loggy-terminal workflows. This AI agent skill supports Claude

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Local PR Review

Premise

A code review must be anchored to expectations. Those expectations come from:

  • Explicit intent sources (PR description, linked tickets, design docs) when available, plus
  • A canonical spec file (author-provided in-repo on the branch when available, otherwise a review spec.md you write) to make expectations explicit and reviewable.

You do not change implementation code. You only write review artifacts.

Outputs (always written to disk)

Every run must produce these artifacts side-by-side:

  • system-design-review.md
  • code-review.md
  • walkthrough.md (must use the /walkthrough workflow from .agents/skills/drive-pr-walkthrough/SKILL.md; override its output path to land next to the other artifacts)

spec.md is only written when the branch does not already contain an in-repo canonical spec file. If a spec exists, do not duplicate it in the review outputs; reference it.

Output location rule:

  • If a canonical spec file exists in-repo on the current branch, write review artifacts next to it (see 2.1).
  • Otherwise (including when the only spec is external/off-branch), write review artifacts under wip/ (local-only scratch; never commit).

1) Establish the review scope (branch + base)

Defaults:

  • Review the current branch.
  • Base is the PR base branch when a GitHub PR exists; otherwise the repo default branch (typically main).

Explicit override rule:

  • If the user specifies a base/parent branch, honor it exactly for the review range.
  • Do not substitute origin/HEAD or origin/main when an explicit base is provided.
  • If the provided name is ambiguous, resolve to origin/<base> when possible and record the resolved range in artifacts.

Steps:

  1. Determine current branch name.
  2. Fetch latest refs from origin.
  3. Resolve base branch:
    • If the user provided a base/parent branch, use it exactly.
    • If the provided name is ambiguous, resolve to origin/<base> when possible and record the resolved range in artifacts.
    • Otherwise, if a PR exists for the current branch, use its baseRefName.
    • Otherwise use the repo default branch (from origin/HEAD, typically main).
  4. Establish the review range:
    • Topic branch: origin/<base>...HEAD
    • If already on default branch: infer best-effort scope from git history and clearly state uncertainty in the reports.

Evidence to capture (for your own analysis):

  • git log --oneline origin/<base>..HEAD
  • git diff --name-only origin/<base>...HEAD
  • git diff origin/<base>...HEAD

PR discovery hints:

  • gh pr view --json number,url,title,body,baseRefName,headRefName
  • Fallback: gh pr list --head <branch> --state all --json number,url,title,body,baseRefName,headRefName --limit 1

2) Establish expectations (use canonical spec or infer one)

2.1) Choose an artifact directory (prefer next to an existing in-repo spec)

First, locate a canonical spec file in-repo on the current branch (preferred inputs first).

Important:

  • A “canonical spec” in this step means a spec file that exists in this repo on this branch.
  • If the user/PR links an external spec (URL, other repo, or a file not present on this branch), treat it as an expectation source (2.2), but it does not control artifact placement.

Preferred inputs:

  1. If the user provided an in-repo spec file path (repo-relative or workspace-absolute) and it exists on this branch, treat it as canonical.
  2. Else, if the GitHub PR body links to or mentions an in-repo spec file path that exists on this branch, treat it as canonical.
  3. Else, search the branch for spec-like docs and pick the best match:
    • Prefer: specs/**/spec.md, projects/**/spec.md
    • Also consider: **/spec.md, **/requirements.md, **/design.md (especially if added/changed in the diff)

Then choose where artifacts go:

  • If an in-repo canonical spec exists:
    • Let SPEC_DIR be the folder containing the spec file.
    • If PR number is available: write to SPEC_DIR/reviews/pr-<PR_NUMBER>/
    • Else: write to SPEC_DIR/reviews/
  • Otherwise (no in-repo canonical spec):
    • If PR number is available: write to wip/review-code/pr-<PR_NUMBER>/
    • Else: write to wip/review-code/branch-<BRANCH_NAME>/

2.2) Gather expectation sources (inputs to your expectations model)

Prefer explicit intent sources over inference from the diff:

  1. Canonical spec file (if present from 2.1)
  2. External/off-branch spec (if provided by the user or linked in the PR body)
  3. GitHub PR title/body
  4. Linear ticket linked in the PR body (preferred), otherwise inferable from branch name (e.g. ABC-123), otherwise absent
  5. New/changed documentation on the branch that clarifies intent/constraints (ADRs, READMEs, docs/**)
  6. The diff itself (last resort for intent)

If the branch includes additional spec-like docs beyond the canonical spec file, treat them as supporting intent sources (not a required format), for example:

  • **/requirements.md, **/design.md
  • Relevant ADRs under docs/architecture docs/adrs/

2.3) Ensure a review spec exists (required)

If an in-repo canonical spec exists (from 2.1), use it as the review spec input and do not write a new one.

If the author has not provided an in-repo canonical spec, infer one and write a review spec.md into the artifact directory (even if an external/off-branch spec exists; treat it as a primary source and link it).

If the spec is inferred, it must begin with a highly visible notice stating:

  • that it was constructed by you (the reviewer), and
  • the sources it was inferred from (PR/Linear/docs/diff), with links/paths.

If you are writing an inferred review spec.md, it must:

  • State whether expectations are explicit (linked docs) vs inferred (from PR/Linear/diff)
  • List sources (PR/Linear/docs) with links/paths
  • Include:
    • Intent
    • Functional requirements
    • Non-goals / out of scope
    • Constraints / invariants / compatibility
    • Acceptance criteria
    • Risks (migration/perf/security/rollout)
  • If a requirement is ambiguous, record it as an explicit assumption or open question.

Linear enrichment:

  • If a Linear ticket link exists and you can fetch it, use it to refine requirements/non-goals/acceptance criteria.

3) Write the system / solution design review

Write system-design-review.md focused on architecture and system design, grounded in the spec and any design docs added/changed on the branch.

Minimum coverage:

  • What problem is being solved; what new guarantees/invariants are introduced
  • Subsystem fit (contracts, plans, runtime, adapters/plugins, capability gating)
  • Boundary correctness (domain/layer/plane imports; deterministic artifacts)
  • ADRs: if the branch adds/changes ADRs under docs/architecture docs/adrs/, treat them as design-intent sources and explicitly review their reasoning/trade-offs
  • Test strategy adequacy at the architectural level (what must be proven, where)

4) Write the code review

Write code-review.md grounded in the spec and the established diff range.

Minimum inputs:

  • Read the repo conventions relevant to the change (at least AGENTS.md + any relevant .cursor/rules/** and package README.md touched by the diff).
  • Read changed files in full when the diff is insufficient to assess correctness, intent, or invariants.

4.1) Review criteria (minimum coverage)

Evaluate changes against:

  • Idiomaticity (language-idiomatic patterns and naming)
  • Best practices & patterns (including project-specific conventions)
  • Clarity & conciseness (readability, naming, unnecessary complexity)
  • Comments & intent (comments explain why, not what; no misleading/outdated comments)
  • Performance (obvious regressions, unnecessary allocations, avoidable extra work)
  • Security (input validation, secrets handling, injection risks, authz/authn enforcement where applicable)
  • Correctness & edge cases (boundary conditions, failure modes, concurrency/reentrancy where relevant)
  • Documentation (public API docs, READMEs, breaking changes, usage examples when appropriate)
  • Tests as evidence of behavior (call out gaps and mismatches with expectations)
  • Acceptance-criteria verification (see 4.5 — verify each AC against code and test assertions, not just map to files)

4.2) Output structure (required)

code-review.md must include these sections at minimum (you may add additional sections as useful):

  • Summary (1–2 sentences)
  • What looks solid (positive notes; can appear near the top)
  • Findings (flat list — everything to address in this PR)
  • Deferred (out of scope) (issues explicitly not addressed because they expand scope beyond what this PR delivers; must state why each is out of scope)
  • Already addressed (table of findings from prior review rounds that have been fixed; include commit hash when available)
  • Acceptance-criteria verification (see 4.5)

Categorization heuristic

Do not use blocking / non-blocking / nits tiers. Agents do implementation — perceived effort is not a useful signal for whether something should be fixed. The only legitimate reason to defer a finding is scope: fixing it would pull in work that belongs to a different PR or milestone. If a finding is in scope, it goes in Findings and gets addressed. If fixing it would expand scope beyond what this PR delivers, it goes in Deferred with a clear reason.

Prioritize findings by impact: security > correctness > performance > maintainability > style.

4.3) Finding format (required)

4.3.1) Finding IDs (required)

All findings must have a unique, unambiguous ID so they can be referenced from other places (follow-up docs, comments, issue trackers).

  • Use a single, globally unique sequence across the entire code-review.md (do not restart numbering per section).
  • Preferred format: F<NN> (e.g. F01, F02, …). All findings and deferred items share the same sequence.

For each finding, include:

  • Location: repo-relative path, and line range as plain text (not inside a path:line markdown link). In Cursor (CURSOR_AGENT, CURSOR_TRACE_ID, or CURSOR_CLI set, or user says output is for Cursor): use a path-only markdown link [path](path) and put the range after it, e.g. — lines 12–34. Outside Cursor, you may use [path (L12–L34)](path:12-34) if links resolve for the reader.
  • Issue: concise description of the problem and why it matters
  • Suggestion: concrete fix or improvement
  • Code example (when helpful): suggested change

For acceptance-criteria verification entries, see 4.5.

4.4) Review boundaries (required)

Do not:

  • Review formatting-only changes (defer to formatters/linters)
  • Nitpick personal preferences that do not affect readability or maintainability
  • Suggest large rewrites when the current approach is acceptable
  • Flag issues in unchanged code unless directly impacted by the change
  • Use absolute filesystem paths in the review

4.5) Acceptance-criteria verification (required)

If the spec (or inferred review spec) contains acceptance criteria, the code review must verify each one against the actual implementation. This is the most important part of the review — it answers "did we build what we said we'd build?"

What "verify" means

Pointing to a file is not verification. For each acceptance criterion:

  1. Read the AC literally. What observable behavior or property does it require?
  2. Find the implementation code that is supposed to satisfy it. Read the code — does it actually do what the AC says?
  3. Find the test(s) that prove it. Read the test assertions — do they actually assert the AC's requirement, or do they assert something weaker?
  4. Assign a verdict: one of PASS, FAIL, NOT VERIFIED, or WEAK.

Verdict definitions:

  • PASS: The implementation satisfies the AC, and a test exists that asserts the specific behavior the AC requires.
  • FAIL: The implementation does not satisfy the AC (missing, incomplete, or incorrect behavior). State what is missing or wrong.
  • NOT VERIFIED: No test or manual evidence exists to confirm the AC. The implementation may look correct by inspection but nothing proves it works. State what verification is missing.
  • WEAK: A test exists but its assertions do not actually prove the AC (e.g. the AC requires byte-identical output but the test only checks object references; the AC requires a specific provider is selected but the test only checks typeof === 'function'). State what the test actually asserts vs. what the AC requires.

Common traps to avoid

  • Mapping, not verifying: Listing a file path next to an AC is not verification. You must read the code and test assertions and confirm they match the AC's requirement.
  • Trusting test names: A test named "selects TypeScript provider" that only asserts typeof source === 'function' does not verify provider selection. Read the assertions, not the test name.
  • Confusing structural equivalence with behavioral equivalence: Checking that two config objects have the same .family reference is not the same as checking that they produce identical emit output.
  • Assuming E2E coverage exists: If an AC requires end-to-end behavior (e.g. "tsc reports no errors"), check whether an E2E test actually exists. If it doesn't, the verdict is NOT VERIFIED regardless of how correct the unit tests look.

Noting the absence of integration/E2E tests

When acceptance criteria describe end-to-end behavior (user runs command → observable outcome), they are most reliably verified by integration or E2E tests that exercise the full stack. If such tests are absent:

  • Flag this explicitly in the verification table.
  • Note it as a finding (not deferred — missing AC evidence is in scope for any PR that claims to deliver those ACs).
  • Recommend the specific integration/E2E tests that would close the gap.

Output format

Include a verification table with a row per AC and a summary count:

markdown
1| AC | Verdict | Detail | 2|---|---|---| 3| AC1: <short statement> | **PASS** / **FAIL** / **NOT VERIFIED** / **WEAK** | <What you checked, what you found, why this verdict> | 4| ... | ... | ... | 5 6### Summary 7 8| Result | Count | ACs | 9|---|---|---| 10| PASS | N | AC2, AC3, ... | 11| FAIL | N | AC1, ... | 12| NOT VERIFIED | N | AC4, ... | 13| WEAK | N | AC8, ... |

5) Write the walkthrough

Write walkthrough.md as a semantic narrative of the change set.

Requirement:

  • Use the /walkthrough workflow from .agents/skills/drive-pr-walkthrough/SKILL.md and override its output path so the file lands next to the review artifacts.

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