fix-p0-issues

# Fix P0 Issues Skill Use this skill to automatically address the highest-priority customer issues by spawning cloud coding agents for each P0 problem identified in the weekly product briefing. ## Workflow ### Step 1: Find the Latest Briefing Resolve the repository root, then find the most recent briefing by sorting filenames (which contain `YYYY-MM-DD` dates). Do **not** use `ls -t` — filesystem modification times are unreliable in freshly cloned repos. ```bash REPO_ROOT=$(git rev-parse --show-toplevel) ls "$REPO_ROOT/reports/weekly_product_briefings/"*.md 2>/dev/null | sort | tail -1 ``` ### Step 2: Extract P0 Issues Parse the briefing for sections starting with `#### P0:`. For each P0, extract: - **Title**: The text after `#### P0:` - **GitHub issue numbers**: Look for `#NNNN` patterns - **Problem description**: The paragraph(s) following the title - **Engineering alignment**: Notes about current engineering investment Example P0 format in briefings: ``` #### P0: Model Selection / Routing Bugs (Trust Issue) Multiple users report... Issues #8724 and #8720 describe... **Engineering alignment:** No commits in the last 2 weeks address model routing. ``` ### Step 3: Research Each P0 For each P0 issue identified: 1. **Fetch GitHub issue details** (if issue numbers are present): ```bash gh issue view <issue_number> --repo YOUR_ORG/YOUR_REPO ``` 2. **Search the codebase** for relevant code using keywords from the issue: - Use grep or semantic search to find related files - Look for error messages, feature names, or component names mentioned in the issue - Identify the likely files/modules that need changes 3. **Document findings**: - List relevant file paths - Note any existing related code or tests - Identify dependencies or related systems ### Step 4: Triage and Confidence Assessment After researching each P0, categorize it into one of the following types and determine whether to spawn an agent: #### Category 1: Inactionable Complaint **Criteria:** The user is complaining about something without: - A specific description of the problem - Reproduction steps - Any indication of how to fix it **Action:** Skip this issue. Do not spawn an agent. Note in your final report that this issue was skipped as inactionable. #### Category 2: Bug Fix **Criteria:** - Clearly scoped problem - Has reproduction steps or clear error description - Narrow scope (affects specific feature/component) - Root cause is identifiable or inferable from the issue **Action:** Spawn a coding agent. These are ideal candidates for automated fixes. #### Category 3: Feature Request **Criteria:** The issue requests new functionality or significant changes to existing behavior. **Action:** Assess confidence before deciding: 1. **Estimate scope**: Small (1-2 files), Medium (3-10 files), Large (10+ files or architectural changes) 2. **Assess complexity**: Is the implementation path clear? Are there existing patterns to follow? 3. **Confidence interval**: Rate 1-5 how likely a coding agent could successfully implement this: - **5 (High)**: Clear requirements, existing patterns, small scope → Spawn agent - **4 (Medium-High)**: Mostly clear, some ambiguity, medium scope → Spawn agent with caveats - **3 (Medium)**: Significant ambiguity or medium-large scope → Note in report, do not spawn - **1-2 (Low)**: Large scope, unclear requirements, or architectural → Skip, note in report **Output format for each P0:** ``` P0: <Title> - Category: <Bug Fix | Feature Request | Inactionable Complaint> - Confidence: <1-5> (for Feature Requests) - Scope: <Small | Medium | Large> (for Feature Requests) - Decision: <Spawn Agent | Skip> - Reasoning: <brief explanation> ``` ### Step 5: Spawn Cloud Agents **IMPORTANT:** You MUST use exactly `oz` to spawn cloud agents. The command must be exactly as shown below. For each P0 that passed triage (Bug Fixes and high-confidence Feature Requests), spawn a cloud coding agent: ```bash oz agent run-cloud \ --environment YOUR_OZ_ENVIRONMENT_ID \ --api-key $WARP_API_KEY \ --prompt "<constructed prompt>" ``` **Do NOT substitute any other binary.** If `oz` is not available, stop and report the error rather than using an alternative. **Prompt construction template:** ``` Fix GitHub issue #<NUMBER>: <TITLE> ## Problem <Problem description from briefing> ## GitHub Issue Details <Details fetched from gh issue view> ## Relevant Code The following files are likely relevant: - <file path 1> - <file path 2> ## Task 1. Investigate the issue in the codebase 2. Implement a fix 3. Add or update tests as appropriate 4. Create a PR with a clear description of the changes ## Context This is a P0 issue affecting users. Prioritize correctness and reliability. ``` ### Step 6: Track and Report After spawning agents, output a summary: ``` === P0 Fix Agents Spawned === P0: <Title 1> - GitHub Issues: #NNNN, #NNNN - Run ID: <run-id-1> - Monitor: oz run get <run-id-1> P0: <Title 2> - GitHub Issues: #NNNN - Run ID: <run-id-2> - Monitor: oz run get <run-id-2> ... To check all runs: oz run list --output-format text ``` ## Agent Environment: Repository Details The cloud agent environment has the primary application repositories pre-installed. Include the relevant context below in your prompts to subagents. Key points: - **your-app-client** (your primary client repo): `/home/user/your-app-client` - **your-app-server** (your primary server/backend repo): `/home/user/your-app-server` ## Guidelines - **Skip P0s already being addressed**: If the briefing notes an active branch exists, skip spawning an agent for that issue - **Limit concurrent agents**: Don't spawn more than 3 agents at once to avoid resource contention - **Include context**: The more context in the prompt, the better the agent can fix the issue - **Prefer targeted fixes**: Each agent should focus on one P0 issue, not multiple ## Example Usage When asked "fix the P0s" or "address critical issues from the briefing": 1. Read `reports/weekly_product_briefings/roadmap_customer_alignment_2026-02-21.md` 2. Find P0s: Login Timeout Errors (#101, #102), Data Export Failures (#103), Slow Dashboard Load (#104, etc.) 3. Skip macOS crash (active branch exists per briefing) 4. Research model routing and UI issues 5. Spawn agents for the actionable P0s 6. Report run IDs