PR Comments — Triage & Fix Fetch all unresolved PR review threads, deduplicate across bots, triage by severity, and produce a fix plan for human approval. After sign-off, resolve ignored threads and spawn subagents to fix real issues. Invocation /pr-comments — auto-detect PR from current branch /pr-comments 608 — specific PR number Phase 1: Fetch Unresolved Threads 1a. Identify the PR

Auto-detect from current branch, or use the provided PR number

gh

pr

view

--json

number,headRepositoryOwner,title,headRefName,baseRefName

1b. Fetch ALL review threads via GraphQL

Use GraphQL to get thread resolution status — this is the only reliable source of truth.

gh api graphql

-f

query

=

'

{

repository(owner: "{OWNER}", name: "{REPO_NAME}") {

pullRequest(number: {PR_NUMBER}) {

reviewThreads(first: 100) {

nodes {

id

isResolved

isOutdated

path

line

comments(first: 20) {

nodes {

databaseId

author

body

path

line

originalLine

createdAt

url

}

}

}

}

}

}

}'

Paginate if

hasNextPage

is true. Collect every thread.

1c. Filter to unresolved threads only

Keep threads where

isResolved == false

Note

isOutdated

— the diff may have moved; flag these for extra scrutiny

1d. Also fetch issue-level comments (PR conversation tab)

gh api

--paginate

"repos/{OWNER}/{REPO_NAME}/issues/{PR_NUMBER}/comments?per_page=100"

Filter to comments from

human reviewers only

(not bots). These are often the most important.

Phase 2: Deduplicate & Classify

Multiple bots often flag the

same underlying issue

on the same file/line. Group them.

2a. Group by file + line range

Threads targeting the same file within a 5-line range likely address the same issue. Merge them into a single logical issue.

2b. Parse severity from bot comments

Each bot uses different severity markers:

Bot

Format

Example

coderabbitai[bot]

Emoji badge in body

🟠 Major

,

🟡 Minor

,

🔴 Critical

gemini-code-assist[bot]

SVG image alt text

![medium]

,

![high]

,

![low]

chatgpt-codex-connector[bot]

Shield badge

P1

,

P2

,

P3

devin-ai-integration[bot]

HTML comment metadata

Parse

devin-review-comment

JSON for severity

Map all to a unified scale:

Critical > Major > Medium > Minor > Nitpick

When multiple bots flag the same issue at different severities, take the

highest

.

2c. Classify each issue

For each deduplicated issue, determine:

Category

:

security

|

bug

|

correctness

|

performance

|

accessibility

|

style

|

config

|

docs

Severity

Critical / Major / Medium / Minor / Nitpick

Confidence

How likely is this a real problem vs. a false positive? Human reviewer comments → always high confidence Multiple bots flagging the same thing → high confidence Single bot, no context about codebase patterns → low confidence Bot flagging a SKILL.md or config file → usually noise 2d. Identify ignore candidates Flag as ignore candidate if ANY of these apply: Bot comment on a non-source file ( .md , config, migrations) with no security implications Style/nitpick-level feedback that contradicts project conventions (check AGENTS.md) Bot flagging something that was intentionally designed that way (check git blame / PR description) Outdated thread ( isOutdated == true ) where the code has already changed Duplicate of another issue already being addressed Bot suggesting a pattern that contradicts a loaded skill or AGENTS.md convention Phase 3: Write the Fix Plan Write the plan to .claude/scratchpad/pr-{PR_NUMBER}-review-plan.md . Plan Format

PR #{PR_NUMBER} Review Plan — "{PR_TITLE}" ** Branch: ** {branch_name} ** PR URL: ** {pr_url} ** Threads fetched: ** {total} total, {unresolved} unresolved, {outdated} outdated ** Bot breakdown: **

Issues to Fix (ordered by severity) Only include issues that will actually be fixed. Items classified as ignored in Phase 2 go EXCLUSIVELY in the Ignored section below — never list them here.

1. [{SEVERITY}]

** File: ** path/to/file.ts#L{line} - ** Category: ** {category} - ** Flagged by: ** @bot1, @bot2 - ** Comment URL: ** {url to first comment} - ** What's wrong: ** {1-2 sentence explanation in plain english} - ** Suggested fix: **

Original comment (from @bot1):

{relevant excerpt — strip boilerplate/badges}

2. [{SEVERITY}] ...

Ignored (with reasoning) Each ignored item appears ONLY here — not duplicated in the Issues to Fix section above.

I1. @{bot} on path/to/file.ts#L{line}

** Why ignored: ** {specific reason — e.g., "contradicts project convention in AGENTS.md to not use explicit return types", "outdated thread, code already changed", "style nitpick on a config file"} - ** Original comment: **

I2. ...

Summary

** {N} issues to fix ** across {M} files - ** {K} comments ignored ** ({reasons breakdown}) - Estimated complexity: {low/medium/high} Present to user After writing the plan, tell the user: Review plan written to .claude/scratchpad/pr-{PR_NUMBER}-review-plan.md . {N} issues to fix , {K} ignored . Please review and confirm to proceed. STOP HERE. Wait for the user to review and approve. Do not proceed until they confirm. Phase 4: Execute (after human approval) Once the user approves (they may edit the plan first — re-read it before executing): 4a. Resolve ignored threads For each ignored issue, resolve the GitHub thread with a brief comment explaining why:

Post a reply comment on the thread

gh api -X POST "repos/{OWNER}/{REPO_NAME}/pulls/{PR_NUMBER}/comments" \ -f body = "Acknowledged — {reason}. Resolving." \ -F in_reply_to = { COMMENT_DATABASE_ID }

Resolve the thread via GraphQL

gh api graphql -f query = ' mutation { resolveReviewThread(input: { threadId: "{THREAD_NODE_ID}" }) { thread { isResolved } } }' Use concise, specific dismiss reasons. Examples: "Acknowledged — project convention is to omit explicit return types (see AGENTS.md). Resolving." "Acknowledged — outdated thread, code has been refactored. Resolving." "Acknowledged — this is intentional; sessionStorage is only accessed client-side. Resolving." 4b. Fix real issues with subagents Group related issues that touch the same file or logical unit. Then launch parallel subagents (one per file or logical group) using the Task tool: Launch a Task subagent (subagent_type: "general-purpose") for each group: Prompt template: "Fix the following PR review issue(s) on branch {BRANCH}: Issue: {description} File: {path}#{line} What's wrong: {explanation} Suggested fix: {fix description} Read the file, understand the surrounding context, and make the fix. After fixing, verify the change is correct. Do NOT touch unrelated code." Use subagent_type: "general-purpose" for each group Launch groups in parallel where they touch different files Sequential if they touch the same file 4c. After all subagents complete Resolve the fixed threads on GitHub (same GraphQL mutation as 4a, with a comment like "Fixed in latest push.") Report results to the user Known Bot Noise Patterns These are almost always ignorable — but verify before dismissing: coderabbit on SKILL.md / AGENTS.md files — flags markdown structure, irrelevant gemini suggesting explicit return types — check project AGENTS.md or lint config before accepting devin HTML comment metadata — often duplicates what coderabbit already found codex P3 style suggestions — usually preferences, not bugs Any bot suggesting as casts or non-null assertions — check project conventions before accepting vercel[bot] deployment comments — pure noise, never actionable Bot comments on migration files — almost always false positives (auto-generated code)