resolve-agent-reviews
Resolve PR review bot findings on current PR. Fetches unanswered bot comments, evaluates each finding, fixes real bugs, dismisses false positives, replies to every comment, and watches for new findings until bots go quiet.
What this skill does
Automatically resolve findings from PR review bots (Copilot, Cursor Bugbot, CodeRabbit, etc.) on the current PR. Uses a two-phase workflow: fix all existing issues, then poll for new ones until bots go quiet.
## Prerequisites
All commands below use `npx agent-reviews`. If the project uses a different package manager, substitute the appropriate runner (e.g., `pnpm dlx agent-reviews` for pnpm, `yarn dlx agent-reviews` for Yarn, `bunx agent-reviews` for Bun). Honor the user's package manager preference throughout.
**Cloud environments only** (e.g., Codespaces, remote agents): verify git author identity so CI checks can map commits to the user. Run `git config --global --get user.email` and if empty or a placeholder, set it manually. Skip this check in local environments.
## Phase 1: FETCH & FIX (synchronous)
### Step 1: Fetch All Bot Comments (Expanded)
Run `npx agent-reviews --bots-only --unanswered --expanded`
The CLI auto-detects the current branch, finds the associated PR, and authenticates via `gh` CLI or environment variables. If anything fails (no token, no PR, CLI not installed), it exits with a clear error message.
This shows only unanswered bot comments with full detail: complete comment body (no truncation), diff hunk (code context), and all replies. Each comment shows its ID in brackets (e.g., `[12345678]`).
If zero comments are returned, print "No unanswered bot comments found" and skip to Phase 2.
### Step 3: Process Each Unanswered Comment
For each comment from the expanded output:
#### A. Evaluate the Finding
Read the referenced code and determine:
1. **TRUE POSITIVE** - A real bug that needs fixing
2. **FALSE POSITIVE** - Not actually a bug (intentional behavior, bot misunderstanding)
3. **UNCERTAIN** - Not sure; ask the user
**Likely TRUE POSITIVE:**
- Code obviously violates stated behavior
- Missing null checks on potentially undefined values
- Type mismatches or incorrect function signatures
- Logic errors in conditionals
- Missing error handling for documented failure cases
**Likely FALSE POSITIVE:**
- Bot doesn't understand the framework/library patterns
- Code is intentionally structured that way (with comments explaining why)
- Bot is flagging style preferences, not bugs
- The "bug" is actually a feature or intentional behavior
- Bot misread the code flow
**When UNCERTAIN -- ask the user:**
- The fix would require architectural changes
- You're genuinely unsure if the behavior is intentional
- The "bug" relates to business logic you don't fully understand
- Multiple valid interpretations exist
- The fix could have unintended side effects
#### B. Act on Evaluation
**If TRUE POSITIVE:** Fix the code. Track the comment ID and a brief description of the fix.
**If FALSE POSITIVE:** Do NOT change the code. Track the comment ID and the reason it's not a real bug.
**If UNCERTAIN:** Ask the user. If they say skip, track it as skipped.
Do NOT reply to comments yet. Replies happen after the commit (Step 5).
### Step 4: Commit and Push
After evaluating and fixing ALL unanswered comments:
1. Run your project's lint and type-check
2. Stage, commit, and push:
```bash
git add -A
git commit -m "fix: address PR review bot findings
{List of bugs fixed, grouped by bot}"
git push
```
3. Capture the commit hash from the output.
### Step 5: Reply to All Comments
Now that the commit hash exists, reply to every processed comment. The `--resolve` flag marks the review thread as resolved on GitHub. Use it only when closing the conversation (false positives and user-skipped findings), not for fixes that reviewers should still verify.
**For each TRUE POSITIVE** (we fixed it; leave the thread open so reviewers/bots can verify):
Run `npx agent-reviews --reply <comment_id> "Fixed in {hash}. {Brief description of the fix}"`
**For each FALSE POSITIVE** (closing the conversation):
Run `npx agent-reviews --reply <comment_id> "Won't fix: {reason}. {Explanation of why this is intentional or not applicable}" --resolve`
**For each SKIPPED** (user chose not to address it):
Run `npx agent-reviews --reply <comment_id> "Skipped per user request" --resolve`
**Non-threadable comments:** If a finding was posted as a PR-level issue comment or review-summary submission (not an inline review comment on a specific line), the CLI cannot post a threaded reply and will print `⊘ Skipped reply: comment is not part of a review thread`. That's expected. Record the outcome in the summary and move on; do not retry.
**DO NOT start Phase 2 until all replies are posted.**
---
## Phase 2: POLL FOR NEW COMMENTS (loop until quiet)
The watcher exits immediately when new comments are found (after a 5s grace period to catch batch posts). This means you run it in a loop: start watcher, process any comments it returns, restart watcher, repeat until the watcher times out with no new comments.
### Step 6: Start Watcher Loop
Repeat the following until the watcher exits with no new comments:
**6a.** Launch the watcher in the background:
Run `npx agent-reviews --watch --bots-only` as a background task.
**6b.** Wait for the background command to complete (default 10 minutes; override with `--timeout`).
**6c.** Check the output:
- **If new comments were found** (output contains `EXITING WITH NEW COMMENTS`):
1. Use `--detail <id>` to read each new comment's full detail
2. Process them exactly as in Phase 1, Steps 3-5 (evaluate, fix, commit, push, reply)
3. **Go back to Step 6a** to restart the watcher
- **If no new comments** (output contains `WATCH COMPLETE`):
Stop looping and move to the Summary Report.
---
## Summary Report
After both phases complete, provide a summary:
```text
## PR Review Bot Resolution Summary
### Results
- Fixed: X bugs
- Already fixed: X bugs
- Won't fix (false positives): X
- Skipped per user: X
### By Bot
#### cursor[bot]
- BUG-001: {description} - Fixed in {commit}
- BUG-002: {description} - Won't fix: {reason}
#### Copilot
- {description} - Fixed in {commit}
### Status
All findings addressed. Watch completed.
```
## Important Notes
### Response Policy
- **Every finding gets a response** - No silent ignores
- Responses help train bots and document decisions
- "Won't fix" responses prevent the same false positive from being re-raised
### User Interaction
- Ask the user when uncertain about a finding
- Don't guess on architectural or business logic questions
- It's better to ask than to make a wrong fix or wrong dismissal
### Best Practices
- Verify findings before fixing - bots have false positives
- Keep fixes minimal and focused - don't refactor unrelated code
- Ensure type-check and lint pass before committing
- Group related fixes into a single commit
- Copilot `suggestion` blocks often contain ready-to-use fixes
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.