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.

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):

   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:

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