# Review Pr

> Review a pull request through multiple quality lenses and present a compiled analysis with inline comments. Use when the user wants a thorough PR review.

- Skill: `atomicinnovation/review-pr` (Agent Skill)
- Install (CLI): `npx skillmds@latest add atomicinnovation/review-pr`
- Raw SKILL.md: https://api.skillmd.com/api/skills/atomicinnovation/review-pr/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: atomicinnovation (https://skillmd.com/u/atomicinnovation)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/atomicinnovation/review-pr

---


# Review PR

!`accelerator config context --skill review-pr --fail-safe`
!`accelerator config agents --fail-safe`

If no "Agent Names" section appears above, use these defaults:
accelerator:reviewer, accelerator:codebase-locator,
accelerator:codebase-analyser, accelerator:codebase-pattern-finder,
accelerator:documents-locator, accelerator:documents-analyser,
accelerator:web-search-researcher.

!`accelerator config review pr --fail-safe`

**PR reviews directory**: !`accelerator config path review_prs --fail-safe`
**Tmp directory**: !`accelerator config path tmp --fail-safe`

**IMPORTANT**: Wherever `{tmp directory}` or `{pr reviews directory}` appears
in the instructions below, substitute the actual resolved path shown above.
Never use `/tmp` or any other path not shown above.

**IMPORTANT**: When composing prompts for sub-agents, resolve all `{...}`
path placeholders to their actual values before passing the prompt —
sub-agents cannot see the bold-label definitions above and have no way to
resolve the placeholders themselves.

## PR Review Template

The template below defines the frontmatter and body structure that every
PR review must carry. Read it now — use it to guide what information
you record in Steps 3-4 and what shape you persist in Step 4.10.

!`accelerator config template pr-review --fail-safe`

You are tasked with reviewing a pull request through multiple quality lenses
and then presenting a compiled analysis of the code changes.

## Initial Response

When this command is invoked:

1. **Check if a PR number or URL was provided**:

- If a PR number or URL was provided as an argument, identify the PR
  immediately
- If optional focus arguments were provided (e.g., "focus on security and
  architecture"), note them for lens selection
- Begin the review process

2. **If no argument provided**, respond with:

```
I'll help you review a pull request. Please provide:
1. The PR number or URL (or I'll check the current branch)
2. (Optional) Focus areas to emphasise (e.g., "focus on security and
   architecture")

Tip: You can invoke this command with arguments:
  `/review-pr 123`
  `/review-pr 123 focus on security and test coverage`
```

Then check if the current branch has a PR:
`gh pr view --json number,url,title,state 2>/dev/null`

If a PR is found on the current branch, offer to review it. If not, wait for
the user's input.

## Available Review Lenses

| Lens               | Lens Skill                    | Focus                                                                  |
|--------------------|-------------------------------|------------------------------------------------------------------------|
| **Architecture**   | `architecture-lens`           | Modularity, coupling, dependency direction, structural drift           |
| **Security**       | `security-lens`               | OWASP Top 10, input validation, auth/authz, secrets, data flows        |
| **Test Coverage**  | `test-coverage-lens`          | Coverage adequacy, assertion quality, test pyramid, anti-patterns       |
| **Code Quality**   | `code-quality-lens`           | Complexity, design principles, error handling, code smells             |
| **Standards**      | `standards-lens`              | Project conventions, API standards, naming, accessibility              |
| **Usability**      | `usability-lens`              | Developer experience, API ergonomics, configuration, onboarding        |
| **Performance**    | `performance-lens`            | Algorithmic efficiency, resource usage, concurrency, caching           |
| **Documentation**  | `documentation-lens`          | Documentation completeness, accuracy, audience fit                     |
| **Database**       | `database-lens`               | Migration safety, schema design, query correctness, integrity          |
| **Correctness**    | `correctness-lens`            | Logical validity, boundary conditions, state management, concurrency   |
| **Compatibility**  | `compatibility-lens`          | API contracts, cross-platform, protocol compliance, deps               |
| **Portability**    | `portability-lens`            | Environment independence, deployment flexibility, vendor lock          |
| **Safety**         | `safety-lens`                 | Data loss prevention, operational safety, protective mechanisms        |

## Process Steps

### Step 1: Identify and Fetch the PR

1. **Get PR metadata**:
   `gh pr view {number} --json number,url,title,state,baseRefName,headRefName`

2. **Create temp directory** at `{tmp directory}/pr-review-{number}` (substituting
   the actual PR number):
   ```bash
   mkdir -p {tmp directory}/pr-review-{number}
   ```

3. **Fetch diff, changed files, PR description, and commit context**:
   ```bash
   gh pr diff {number} > {tmp directory}/pr-review-{number}/diff.patch
   gh pr diff {number} --name-only > {tmp directory}/pr-review-{number}/changed-files.txt
   gh pr view {number} --json body --jq '.body' > {tmp directory}/pr-review-{number}/pr-description.md
   gh pr view {number} --json commits --jq '.commits[].messageHeadline' > {tmp directory}/pr-review-{number}/commits.txt
   ```

4. **Read the diff, changed files list, PR description, and commits** to
   understand scope and intent.

5. **Fetch additional metadata for the Reviews API**:
   ```bash
   gh api repos/{owner}/{repo}/pulls/{number} --jq '.head.sha' > {tmp directory}/pr-review-{number}/head-sha.txt
   ```
   ```bash
   accelerator collaboration pr base-repo {number} > {tmp directory}/pr-review-{number}/repo-info.txt
   ```

   Where `{owner}` and `{repo}` are extracted from the PR metadata already
   fetched in step 1.

**Error handling**: If any `gh` command fails, handle these cases:

- **`gh` not installed or not authenticated**: Inform the user that the `gh`
  CLI is required and suggest running `gh auth login` to authenticate.
- **No default remote repository (`gh`-specific)**: Instruct the user to run
  `gh repo set-default` and select the appropriate repository (mirrors the
  pattern in `/describe-pr`) — this is `gh`'s own default-repo setting,
  distinct from the `collaboration` binary's own `origin`-remote-based
  resolution below.
- **Cannot determine base repo owner/name**: If `accelerator collaboration
  pr base-repo` exits non-zero, surface its stderr verbatim (non-zero exit;
  exit code 2 for a usage/refusal such as no `origin` remote configured,
  1 for any other failure, e.g. a GitHub API error).
- **Invalid PR number or PR not found**: Inform the user that the PR could not
  be found and suggest checking the number. If on a branch with no PR, list
  open PRs with `gh pr list --limit 10` and ask the user to select one.
- **Empty diff**: If `diff.patch` is empty (e.g., a draft PR with no changes),
  inform the user and use the `AskUserQuestion` tool with two options:
  1. **Yes, review description and commits only** — proceed without a diff
  2. **No, abort** — exit without reviewing

### Step 2: Select Review Lenses

Determine which lenses are relevant based on the PR's scope and any
user-provided focus arguments.

**If the user provided focus arguments:**

- Map the focus areas to the corresponding lenses
- Include any additional lenses that are clearly relevant to the PR's scope
- Briefly explain which lenses you're running and why

**If no focus arguments were provided, auto-detect relevance:**

Take time to think carefully about which lenses apply based on:

- **Architecture** — relevant for most PRs; skip only for trivial single-file
  changes
- **Security** — relevant when changes involve: user input handling, auth/authz,
  data storage, external integrations, API endpoints, secrets/config
- **Test Coverage** — relevant for most PRs; skip only for documentation-only
  or configuration-only changes
- **Code Quality** — relevant for most PRs; skip only for documentation-only
  changes
- **Standards** — relevant when changes involve: API changes, new files/modules,
  public interfaces, naming-heavy changes
- **Usability** — relevant when changes involve: public APIs, CLI interfaces,
  configuration surfaces, breaking changes, developer-facing libraries
- **Performance** — relevant when changes involve: data processing, API
  endpoints handling load, algorithm-heavy code, concurrency resource
  efficiency, caching logic, or hot code paths. Skip for documentation-only,
  configuration-only, or simple UI changes.
- **Documentation** — relevant when changes involve: public APIs, README
  files, configuration surfaces, new features that need documentation,
  breaking changes requiring migration guides. Skip for internal refactoring
  with no interface changes.
- **Database** — relevant when changes involve: database migrations, schema
  changes, new queries, ORM model changes, transaction logic, connection
  pool configuration. Skip for changes with no database interaction.
- **Correctness** — relevant for most PRs; skip only for documentation-only,
  configuration-only, or simple renaming changes.
- **Compatibility** — relevant when changes involve: public API
  modifications, dependency updates, serialisation format changes,
  cross-platform code, protocol implementations. Skip for internal-only
  changes with no external consumers.
- **Portability** — relevant when changes involve: infrastructure
  configuration, deployment scripts, containerisation, cloud provider
  integrations, environment-specific code paths. Skip for application logic
  with no environment dependencies.
- **Safety** — relevant when changes involve: data deletion or modification
  operations, deployment configuration, automated batch processes,
  infrastructure changes, feature flags, or critical system components.
  Skip for read-only features, documentation, or UI-only changes.

**Lens selection cap:** Select the most relevant lenses for the change under
review. If review configuration is provided above, use the configured
`min_lenses` and `max_lenses` values. Otherwise, use the defaults: 
**{min lenses} to {max lenses}** lenses. Apply these prioritisation rules:

Apply this lens selection pipeline in order:

1. **Start with all available lenses**: the 13 built-in lenses plus any
   custom lenses listed in the review configuration above.
2. **Remove disabled lenses**: if review configuration specifies
   `disabled_lenses`, remove those from the available set. They are never
   selected regardless of auto-detect criteria.
3. **Mark core lenses**: if review configuration specifies `core_lenses`,
   use that list. Otherwise, the core lenses are Architecture, Code Quality,
   Test Coverage, and Correctness. Core lenses are included unless the change
   is clearly outside their scope.
4. **Auto-detect remaining lenses**: use the criteria below (for built-in
   lenses) and the auto-detect criteria from review configuration (for custom
   lenses) to identify which non-core lenses are relevant to the change.
   Custom lenses that provide auto-detect criteria participate in selection
   like any other non-core lens. Custom lenses without auto-detect criteria
   (marked "always include" in the configuration) are always selected. Custom
   lenses use absolute paths instead of the `${CLAUDE_PLUGIN_ROOT}` lens
   path template.
5. **Apply focus arguments**: if the user provided focus areas, prioritise
   the corresponding lenses and fill remaining slots with auto-detected ones.
6. **Cap at `max_lenses`**: if more lenses than the configured maximum pass
   selection, rank by relevance and drop the least relevant. Prefer lenses
   whose core responsibilities directly overlap with the change's concerns.
7. **Enforce `min_lenses` floor**: never run fewer than `min_lenses` unless
   the change is trivially scoped.

When presenting the lens selection, clearly indicate which lenses are
selected and which are skipped, with a brief reason for each skip.

Present lens selection to the user before proceeding:

```
Based on the PR's scope, I'll review through these lenses:
- Architecture: [reason]
- Security: [reason — or "Skipping: no security-sensitive changes identified"]
- Test Coverage: [reason]
- Code Quality: [reason]
- Standards: [reason — or "Skipping: ..."]
- Usability: [reason — or "Skipping: ..."]
- Performance: [reason — or "Skipping: no performance-sensitive changes identified"]
- Documentation: [reason — or "Skipping: ..."]
- Database: [reason — or "Skipping: no database changes identified"]
- Correctness: [reason]
- Compatibility: [reason — or "Skipping: ..."]
- Portability: [reason — or "Skipping: ..."]
- Safety: [reason — or "Skipping: ..."]

```

Then use the `AskUserQuestion` tool to ask the user whether to proceed, with
two options:

1. **Yes, use the proposed lenses** — run the review with the selected lenses
2. **No, specify which lenses to use** — adjust the selection before running

Wait for the user's answer before spawning reviewers. If they choose option 2,
ask which lenses they want using a **plain-text question only** — do NOT use
`AskUserQuestion` for this follow-up (the lens list is too large for the
4-option limit). If any lens name is unrecognised, seek clarification. Once
confirmed, update the selection and re-present it using the same
`AskUserQuestion` proceed/adjust pattern. This loop is user-controlled with
no hard termination limit.

### Step 3: Spawn Review Agents

For each selected lens, spawn the {reviewer agent} agent with a prompt
that includes paths to the lens skill and output format files. Do NOT read
these files yourself — the agent reads them in its own context.

**Reminder**: In the template below, replace `{tmp directory}` with the
actual path resolved at the top of this skill before passing the prompt to
the agent.

Compose each agent's prompt following this template:

```
You are reviewing pull request changes through the [lens name] lens.

## Context

The PR artefacts are in the temp directory at {tmp directory}/pr-review-{number}:
- `diff.patch` — the full diff
- `changed-files.txt` — list of changed file paths
- `pr-description.md` — PR description
- `commits.txt` — commit messages

PR number: [number]

## Analysis Strategy

1. Read your lens skill and output format files (see paths below)
2. Read `diff.patch` and `changed-files.txt` from the temp directory
3. Read `pr-description.md` and `commits.txt` for intent context
4. Explore the codebase to understand the architectural landscape around
   the changes
5. Evaluate the changes through your lens, applying each key question
6. Identify beyond-the-diff impact — trace how changes affect consumers
7. Anchor findings to precise diff line numbers (lines must be within
   diff hunks)

## Lens

Read the lens skill at the path listed in the Lens Catalogue table in the
review configuration above. If no review configuration is present, use:
${CLAUDE_PLUGIN_ROOT}/skills/review/lenses/[lens]-lens/SKILL.md

## Output Format

Read the output format at: ${CLAUDE_PLUGIN_ROOT}/skills/review/output-formats/pr-review-output-format/SKILL.md

IMPORTANT: Return your analysis as a single JSON code block. Do not include
prose outside the JSON block.
```

Spawn all selected agents **in parallel** using the Task tool with
`subagent_type: "!`accelerator config agent reviewer --fail-safe`"`.

**IMPORTANT**: Wait for ALL review agents to complete before proceeding.

**Handling malformed agent output**:

If an agent's response is not a clean JSON block, apply this extraction
strategy:

1. Look for a JSON code block fenced with triple backticks (optionally with
   a `json` language tag)
2. If found, extract and parse the content within the fences
3. If the extracted JSON is valid, use it normally
4. If no JSON code block is found, or the JSON within it is invalid, apply
   the fallback: treat the agent's entire output as a single general finding
   with the agent's lens name and `"major"` severity, and include it in the
   review summary body

When falling back, warn the user that the agent's output could not be parsed
and present the raw agent output in a collapsed form so the user can see what
the agent actually found.

### Step 4: Aggregate and Curate Findings

Once all reviews are complete:

1. **Parse agent outputs**: Extract the JSON block from each agent's response
   (see the extraction strategy in Step 3). Collect the `summary`, `strengths`,
   `comments`, and `general_findings` arrays from each.

2. **Aggregate across agents**:
   - Combine all `comments` arrays into a single list
   - Combine all `general_findings` arrays into a single list
   - Combine all `strengths` arrays into a single list
   - Collect all `summary` strings

3. **Validate line numbers against the diff**: Parse the hunk headers in
   `diff.patch` to build valid line ranges per file. For each `@@` header:
   - Extract the new-file range from `@@ -a,b +c,d @@` — lines `c` through
     `c+d-1` are valid RIGHT-side lines
   - Extract the old-file range — lines `a` through `a+b-1` are valid
     LEFT-side lines
   - For each comment in the aggregated `comments` list, check that its
     `path`/`line`/`side` falls within a valid range for that file
   - Move any comments with out-of-range lines to `general_findings`
     automatically, preserving all their metadata (severity, lens, title, body)
   - If a comment was moved, note it in the preview so the user knows

4. **Deduplicate inline comments**: Where multiple agents flag the same file,
   same side, and overlapping or adjacent line range (same path, lines within
   the configured dedup proximity ({dedup proximity}) of each other), consider 
   merging — but only when the findings address the same underlying concern 
   from different lens perspectives. Spatial proximity alone is not sufficient; 
   the findings must be semantically related.

   When merging:
   - Combine the bodies, attributing each part to its lens
   - Use the highest severity among the merged findings
   - Use the highest confidence among the merged findings
   - Note all contributing lenses in the title

   When in doubt, keep comments separate — distinct inline comments are easier
   to resolve individually on GitHub than a merged comment covering multiple
   concerns.

5. **Prioritise and cap inline comments**:
   - Sort by severity: critical > major > minor > suggestion
   - Within the same severity, sort by confidence: high > medium > low
   - Always include all critical findings, even if that exceeds 
     {max inline comments}
   - Select up to the configured max inline comments ({max inline comments}) 
     comments total for inline posting (more if all critical findings push 
     beyond the cap)
   - Move any remaining comments to the summary body as an "Additional
     Findings" list (title + file:line only)

6. **Determine suggested verdict**:

   If review configuration provides verdict overrides above, apply those
   thresholds instead of the defaults below:
   - If `pr_request_changes_severity` is `none`, skip this rule (never
     suggest REQUEST_CHANGES based on severity)
   - If any findings at or above the configured `pr_request_changes_severity`
     (default: `critical`) exist → suggest `REQUEST_CHANGES`
   - If only findings below that threshold → suggest `COMMENT`
   - If no findings at all (only strengths) → suggest `APPROVE`

7. **Identify cross-cutting themes**: Look for findings that appear across
   multiple lenses — issues flagged by 2+ agents reinforce each other and
   should be highlighted in the summary. Also identify tradeoffs where
   different lenses conflict (e.g., security wants more validation, usability
   wants less friction).

8. **Compose the review summary body** (this becomes the `body` field of the
   GitHub review):

   ```markdown
   ## Code Review: #{number} - {title}

   **Verdict:** [APPROVE | REQUEST_CHANGES | COMMENT]

   [Combined assessment: take each agent's summary and synthesise into 2-3
   sentences covering the overall quality of the PR across all lenses]

   ### Cross-Cutting Themes
   [Issues that multiple lenses identified — these deserve the most attention]
   - **[Theme]** (flagged by: [lenses]) — [description]

   ### Tradeoff Analysis
   [Where different lenses disagree, present both perspectives]
   - **[Quality A] vs [Quality B]**: [description and recommendation]

   [Omit either section if there are no cross-cutting themes or tradeoffs]

   ### Strengths
   - ✅ [Aggregated and deduplicated strengths from all agents]

   ### General Findings
   - [emoji] **[Lens]**: [General findings from all agents, sorted by severity]

   ### Additional Findings
   [Only if more than {max inline comments} inline comments were produced and 
   some were deferred]
   - [emoji] `file:line` — [title] ([lens])

   ---
   *Review generated by /review-pr*
   ```

9. **Compose each inline comment body**: Each comment's `body` field should
   already be self-contained from the agent output. For merged comments,
   combine the bodies with a blank line separator and attribute each section
   to its lens.

10. **Write the review artifact** to `{pr reviews directory}/`:

    Determine the next review number:
    ```bash
    mkdir -p {pr reviews directory}
    # Glob for existing reviews of this PR
    ls {pr reviews directory}/{number}-review-*.md 2>/dev/null
    # Extract the highest number, increment by 1. If none exist, use 1.
    ```

    Write the review document to `{pr reviews directory}/{number}-review-{N}.md`.

#### Populate frontmatter

The `target:` field is filled automatically from the PR number — this is
what makes the review traceable back to the PR it covers. Per ADR-0034,
the typed-linkage form is `"pr:<pr-number>"`.

Before writing the PR review file, capture metadata and substitute the
unified base fields and per-type extras into the template's frontmatter
block:

1. Invoke `accelerator corpus metadata derive`
   to obtain `Current Date/Time (UTC):`.
2. **Substitute** every field below with the indicated value:
   - `type:` ← `pr-review`
   - `id:` ← `{number}-review-{N}` (the review filename stem, where
     `{number}` is the PR number and `{N}` is the next review
     number), always quoted as a YAML string
   - `title:` ← the PR title from `gh pr view --json title`
   - `date:` ← the `Current Date/Time (UTC):` value
   - `author:` ← the author value resolved per `create-work-item/SKILL.md:578-580`
   - `producer:` ← `review-pr`
   - `status:` ← `complete`
   - `last_updated:` ← the same `Current Date/Time (UTC):` value
   - `last_updated_by:` ← the same value resolved for `author`
   - `schema_version:` ← `1` (bare integer, not quoted)
   - `parent:` ← typed-linkage ref to the parent PR (`"pr:NNNN"`).
     Fill when the review names a parent; otherwise omit the key.
   - `target:` ← `"pr:<pr-number>"` (e.g. `"pr:123"`); the
     typed-linkage ref to the PR under review per ADR-0034, must
     match the regex `^"pr:[0-9]+"$`. Always fill — every review has
     a target.
   - `relates_to:` ← list of typed-linkage refs to related reviews or
     artifacts (`["pr-review:NNNN", ...]`). Fill when prior reviews
     are explicit; otherwise omit the key.
   - `reviewer:` ← the reviewer value resolved per `create-work-item/SKILL.md:578-580`
   - `verdict:` ← the verdict from Step 4.6 (`APPROVE | REQUEST_CHANGES | COMMENT`)
   - `lenses:` ← the list of lens names used
   - `review_number:` ← `N` (the next available review number from the
     glob above)
   - `pr_number:` ← the PR number from `gh pr view --json number`
     (bare integer; foreign reference to the external PR per
     ADR-0033 §Identity-value shape contract)

   The PR title is recorded in the base `title:` field; no separate
   `pr_title:` field is emitted (the unified schema uses the base
   `title:` for all artifact titles per ADR-0033). The `review_pass:`
   field is intentionally absent — `review-pr` has no in-place
   re-review update flow today; re-running it produces a fresh
   `-review-{N+1}.md`.
3. Write the file with the substituted frontmatter block, followed by
   the review summary composed in Step 4.8 and the inline comments
   and per-lens results sections:

```markdown
{The full review summary from Step 4.8}

## Inline Comments

### `{path}:{line}` — {title}
**Severity**: {severity} | **Confidence**: {confidence} | **Lens**: {lens}

{comment body}

---

### `{path}:{line}` — {title}
...

## Per-Lens Results

### {Lens 1 Name}

**Summary**: {agent summary}

**Strengths**:
{agent strengths}

**Comments**:
{agent comments — each with path, line, severity, confidence, and body}

**General Findings**:
{agent general findings}

### {Lens 2 Name}

...
```

This review artifact captures the complete analysis. The GitHub review
(posted in Step 6) may be a curated subset (capped at ~{max inline comments}
inline comments), but the persistent artifact retains everything.

### Step 5: Present the Review

Present a two-part preview showing exactly what will be posted to the PR:

**Part 1: Review summary** (will become the review's body):

Show the composed summary from Step 4.8 in a markdown code block so the user
can see exactly what will be posted.

**Part 2: Inline comments** (will be attached to specific diff lines):

```
## Proposed Inline Comments ([count] comments)

### [file path 1]
- Line [N]: [emoji] **[Lens]** — [title]
  > [First 1-2 sentences of body as preview]

- Lines [N-M]: [emoji] **[Lens]** — [title]
  > [First 1-2 sentences of body as preview]

### [file path 2]
- Line [N]: [emoji] **[Lens]** — [title]
  > [First 1-2 sentences of body as preview]

[If comments were deferred due to the ~{max inline comments} cap:]
### Deferred to summary ([count] findings)
- [emoji] [Lens]: [title] — `file:line`
```

### Step 6: Offer Actions

After presenting the preview:

```
The review is ready. Would you like to:
1. Post the review? (summary + [count] inline comments, verdict: [suggested verdict])
2. Change the verdict? (currently: [suggested verdict])
3. Edit or remove specific inline comments before posting?
4. Discuss any findings in more detail?
5. Re-run specific lenses with adjusted focus?
```

**When the user chooses to post** (option 1):

1. Read the HEAD SHA and repo info from the temp directory at
   `{tmp directory}/pr-review-{number}/head-sha.txt` and
   `{tmp directory}/pr-review-{number}/repo-info.txt` using the Read tool.

2. Construct the review payload as a JSON object containing:
   - `commit_id`: the HEAD SHA
   - `body`: the review summary composed in Step 4.8
   - `event`: the verdict (`"COMMENT"`, `"REQUEST_CHANGES"`, or `"APPROVE"`)
   - `comments`: array of inline comment objects, each with:
     - `path`: file path from the agent's comment
     - `line`: line number from the agent's comment
     - `side`: side from the agent's comment
     - `body`: the self-contained comment body
     - `start_line` and `start_side`: included only if `end_line` is not null.
       For multi-line comments, the agent's fields map to the API's fields
       with an inversion (see "Multi-Line Comment API Mapping" in Phase 1):
       - API `start_line` ← agent's `line` (the beginning of the range)
       - API `start_side` ← agent's `side`
       - API `line` ← agent's `end_line` (the end of the range)
       - API `side` ← agent's `side`

       Example: agent `{line: 10, end_line: 15, side: "RIGHT"}` becomes
       API `{start_line: 10, start_side: "RIGHT", line: 15, side: "RIGHT"}`

3. Write the review payload JSON to
   `{tmp directory}/pr-review-{number}/review-payload.json`, then post the
   review:
   ```bash
   gh api repos/{owner}/{repo}/pulls/{number}/reviews \
     --method POST --input {tmp directory}/pr-review-{number}/review-payload.json
   ```

   Where `{owner}/{repo}` are the values read from `repo-info.txt`.

4. Confirm success and show the PR URL:
   ```bash
   gh pr view {number} --json url --jq '.url'
   ```

**If the API returns a 422 error** (typically an invalid line reference or
stale commit):
- Report the error to the user
- If the error indicates an invalid line reference, identify which comment(s)
  caused the failure and offer to retry without them (move them to the summary)
- If the error indicates a stale `commit_id` (the PR's HEAD has changed since
  the review started), re-fetch the HEAD SHA and warn the user that new commits
  were pushed. Offer to retry with the updated SHA, noting that line numbers
  may have shifted and some comments may now be invalid

**When the user chooses to edit comments** (option 3):
- Present each comment with a number
- Allow the user to remove specific comments by number
- Allow the user to edit a comment's body text
- After edits, re-present the preview and offer the same action options

**When the user changes the verdict** (option 2):
- Use the `AskUserQuestion` tool with three options:
  1. **APPROVE** — approve the PR
  2. **COMMENT** — leave a non-blocking comment review
  3. **REQUEST_CHANGES** — request changes before merge
- Update the summary body and re-present the preview

## Important Guidelines

1. **Read the diff before doing anything else** — you need complete context to
   select lenses and brief the agents properly

2. **Spawn agents in parallel** — the review lenses are independent and should
   run concurrently for efficiency

3. **Synthesise, don't concatenate** — your value is in compiling a balanced
   view across lenses, identifying themes and tradeoffs, and prioritising
   actionable recommendations. Don't just paste seven reports together.

4. **Be balanced** — highlight strengths alongside concerns. A PR that makes
   good architectural decisions but has security gaps should get credit for
   both.

5. **Prioritise by impact** — structural issues that are hard to fix later
   matter more than surface-level concerns. A critical finding from one lens
   outweighs minor findings from all seven.

6. **Respect tradeoffs** — when lenses conflict, present both sides and let the
   user decide. Don't privilege one quality attribute over another without
   justification.

7. **Clean up temp directory only at session end** — agents may need to
   re-reference the PR context during follow-up discussion.

   The `{tmp directory}/pr-review-{number}/` directory contains ephemeral
   working data (diff, changed-files, PR description, commits, head SHA,
   repo info, review payload JSON) used during the review session. The review
   itself (summary, inline comments, per-lens results) is persisted separately
   to `{pr reviews directory}/{number}-review-{N}.md`.

8. **Handle API errors gracefully** — if the review post fails due to invalid
   line references, identify the problematic comments and offer to retry
   without them rather than failing entirely

9. **Cap inline comments** — if agents produce more findings, prioritise
   critical and major severity. Use the configured max ({max inline comments}).
   Always include all critical findings even if that exceeds the cap. Move 
   overflow to the summary body. This prevents PR comment spam.

10. **Keep positive feedback in the summary** — strengths and good observations
    go in the review body, never as inline comments. Inline comments are
    exclusively for actionable findings.

11. **Use emoji severity prefixes consistently** — 🔴 critical, 🟡 major,
    🔵 minor/suggestion, ✅ strengths. **IMPORTANT**: Use the actual Unicode
    emoji characters (🔴 🟡 🔵 ✅), NOT text shortcodes like `:red_circle:`,
    `:yellow_circle:`, `:blue_circle:`, or `:white_check_mark:`. Shortcodes
    are not rendered in markdown and will appear as literal text.

## What NOT to Do

- Don't skip writing the review artifact — always persist to
  {pr reviews directory}/ so the full analysis is available to the team
- Don't post inline comments for positive feedback — strengths go in the
  summary only
- Don't post more than the configured max inline comments 
  ({max inline comments}) inline comments — prioritise by severity (always 
  include all critical findings even if that exceeds the cap)
- Don't post generic or vague inline comments — each must be specific and
  actionable
- Don't skip the preview step — always show the user what will be posted
  before posting
- Don't skip the lens selection step — always confirm with the user which
  lenses will run
- Don't present raw agent output — always aggregate and curate into the
  structured format
- Don't run lenses that clearly aren't relevant
- Don't modify any code — this is a read-only review

## Relationship to Other Commands

The PR review sits in the development lifecycle alongside other commands:

1. `/create-plan` — Create the implementation plan
2. `/review-plan` — Review and iterate the plan quality
3. `/implement-plan` — Execute the approved plan
4. `/validate-plan` — Verify implementation matches the plan
5. `/describe-pr` — Generate PR description
6. `/review-pr` — Review the PR through quality lenses (this command)

!`accelerator config instructions review-pr --fail-safe`

