triage
This skill should be used when triaging and categorizing findings for the CLI todo system.
Best use case
triage is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
This skill should be used when triaging and categorizing findings for the CLI todo system.
Teams using triage should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/triage/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How triage Compares
| Feature / Agent | triage | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
This skill should be used when triaging and categorizing findings for the CLI todo system.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# triage
- First set the /model to Haiku
- Then read all pending todos in the todos/ directory
Present all findings, decisions, or issues here one by one for triage. The goal is to go through each item and decide whether to add it to the CLI todo system.
**IMPORTANT: DO NOT CODE ANYTHING DURING TRIAGE!**
This command is for:
- Triaging code review findings
- Processing security audit results
- Reviewing performance analysis
- Handling any other categorized findings that need tracking
## Workflow
### Step 1: Present Each Finding
For each finding, present in this format:
```
---
Issue #X: [Brief Title]
Severity: 🔴 P1 (CRITICAL) / 🟡 P2 (IMPORTANT) / 🔵 P3 (NICE-TO-HAVE)
Category: [Security/Performance/Architecture/Bug/Feature/etc.]
Description:
[Detailed explanation of the issue or improvement]
Location: [file_path:line_number]
Problem Scenario:
[Step by step what's wrong or could happen]
Proposed Solution:
[How to fix it]
Estimated Effort: [Small (< 2 hours) / Medium (2-8 hours) / Large (> 8 hours)]
---
Do you want to add this to the todo list?
1. yes - create todo file
2. next - skip this item
3. custom - modify before creating
```
### Step 2: Handle User Decision
**When user says "yes":**
1. **Update existing todo file** (if it exists) or **Create new filename:**
If todo already exists (from code review):
- Rename file from `{id}-pending-{priority}-{desc}.md` → `{id}-ready-{priority}-{desc}.md`
- Update YAML frontmatter: `status: pending` → `status: ready`
- Keep issue_id, priority, and description unchanged
If creating new todo:
```
{next_id}-ready-{priority}-{brief-description}.md
```
Priority mapping:
- 🔴 P1 (CRITICAL) → `p1`
- 🟡 P2 (IMPORTANT) → `p2`
- 🔵 P3 (NICE-TO-HAVE) → `p3`
Example: `042-ready-p1-transaction-boundaries.md`
2. **Update YAML frontmatter:**
```yaml
---
status: ready # IMPORTANT: Change from "pending" to "ready"
priority: p1 # or p2, p3 based on severity
issue_id: "042"
tags: [category, relevant-tags]
dependencies: []
---
```
3. **Populate or update the file:**
```yaml
# [Issue Title]
## Problem Statement
[Description from finding]
## Findings
- [Key discoveries]
- Location: [file_path:line_number]
- [Scenario details]
## Proposed Solutions
### Option 1: [Primary solution]
- **Pros**: [Benefits]
- **Cons**: [Drawbacks if any]
- **Effort**: [Small/Medium/Large]
- **Risk**: [Low/Medium/High]
## Recommended Action
[Filled during triage - specific action plan]
## Technical Details
- **Affected Files**: [List files]
- **Related Components**: [Components affected]
- **Database Changes**: [Yes/No - describe if yes]
## Resources
- Original finding: [Source of this issue]
- Related issues: [If any]
## Acceptance Criteria
- [ ] [Specific success criteria]
- [ ] Tests pass
- [ ] Code reviewed
## Work Log
### {date} - Approved for Work
**By:** Claude Triage System
**Actions:**
- Issue approved during triage session
- Status changed from pending → ready
- Ready to be picked up and worked on
**Learnings:**
- [Context and insights]
## Notes
Source: Triage session on {date}
```
4. **Confirm approval:** "✅ Approved: `{new_filename}` (Issue #{issue_id}) - Status: **ready** → Ready to work on"
**When user says "next":**
- **Delete the todo file** - Remove it from todos/ directory since it's not relevant
- Skip to the next item
- Track skipped items for summary
**When user says "custom":**
- Ask what to modify (priority, description, details)
- Update the information
- Present revised version
- Ask again: yes/next/custom
### Step 3: Continue Until All Processed
- Process all items one by one
- Track using TodoWrite for visibility
- Don't wait for approval between items - keep moving
### Step 4: Final Summary
After all items processed:
````markdown
## Triage Complete
**Total Items:** [X] **Todos Approved (ready):** [Y] **Skipped:** [Z]
### Approved Todos (Ready for Work):
- `042-ready-p1-transaction-boundaries.md` - Transaction boundary issue
- `043-ready-p2-cache-optimization.md` - Cache performance improvement ...
### Skipped Items (Deleted):
- Item #5: [reason] - Removed from todos/
- Item #12: [reason] - Removed from todos/
### Summary of Changes Made:
During triage, the following status updates occurred:
- **Pending → Ready:** Filenames and frontmatter updated to reflect approved status
- **Deleted:** Todo files for skipped findings removed from todos/ directory
- Each approved file now has `status: ready` in YAML frontmatter
### Next Steps:
1. View approved todos ready for work:
```bash
ls todos/*-ready-*.md
```
````
2. Start work on approved items with `wf-develop`.
3. Or pick individual items to work on
4. As you work, update todo status:
- Ready → In Progress (in your local context as you work)
- In Progress → Complete (rename file: ready → complete, update frontmatter)
```
## Example Response Format
```
---
Issue #5: Missing Transaction Boundaries for Multi-Step Operations
Severity: 🔴 P1 (CRITICAL)
Category: Data Integrity / Security
Description: The google_oauth2_connected callback in GoogleOauthCallbacks concern performs multiple database operations without transaction protection. If any step fails midway, the database is left in an inconsistent state.
Location: app/controllers/concerns/google_oauth_callbacks.rb:13-50
Problem Scenario:
1. User.update succeeds (email changed)
2. Account.save! fails (validation error)
3. Result: User has changed email but no associated Account
4. Next login attempt fails completely
Operations Without Transaction:
- User confirmation (line 13)
- Waitlist removal (line 14)
- User profile update (line 21-23)
- Account creation (line 28-37)
- Avatar attachment (line 39-45)
- Journey creation (line 47)
Proposed Solution: Wrap all operations in ApplicationRecord.transaction do ... end block
Estimated Effort: Small (30 minutes)
---
Do you want to add this to the todo list?
1. yes - create todo file
2. next - skip this item
3. custom - modify before creating
```
## Important Implementation Details
### Status Transitions During Triage
**When "yes" is selected:**
1. Rename file: `{id}-pending-{priority}-{desc}.md` → `{id}-ready-{priority}-{desc}.md`
2. Update YAML frontmatter: `status: pending` → `status: ready`
3. Update Work Log with triage approval entry
4. Confirm: "✅ Approved: `{filename}` (Issue #{issue_id}) - Status: **ready**"
**When "next" is selected:**
1. Delete the todo file from todos/ directory
2. Skip to next item
3. No file remains in the system
### Progress Tracking
Every time you present a todo as a header, include:
- **Progress:** X/Y completed (e.g., "3/10 completed")
- **Estimated time remaining:** Based on how quickly you're progressing
- **Pacing:** Monitor time per finding and adjust estimate accordingly
Example:
```
Progress: 3/10 completed | Estimated time: ~2 minutes remaining
```
### Do Not Code During Triage
- ✅ Present findings
- ✅ Make yes/next/custom decisions
- ✅ Update todo files (rename, frontmatter, work log)
- ❌ Do NOT implement fixes or write code
- ❌ Do NOT add detailed implementation details
- ❌ That's for the implementation phase (`wf-develop`)
```
When done give these options
```markdown
What would you like to do next?
1. run `wf-develop` to resolve the todos
2. commit the todos
3. nothing, go chill
```Related Skills
skill-creator
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
modular-skills-architect
Map and refactor an agent context ecosystem: skills, commands/workflows, hooks, agent files, AGENTS.md templates, and docs. Output system map, module/dependency design, Register updates, and a concrete split/consolidate/rename/delete plan. Use when routing or ownership is messy.
heal-skill
This skill should be used when fixing incorrect SKILL.md files with outdated instructions or APIs.
create-agent-skills
Expert guidance for creating, writing, and refining Claude Code Skills. Use when working with SKILL.md files, authoring new skills, improving existing skills, or understanding skill structure and best practices.
agent-native-audit
Comprehensive agent-native architecture audit with scored principles and multi-slice review. Use for system-wide health checks or periodic audits.
write-judge-prompt
Design LLM-as-Judge evaluators for subjective criteria that code-based checks cannot handle. Use when a failure mode requires interpretation (tone, faithfulness, relevance, completeness). Do NOT use when the failure mode can be checked with code (regex, schema validation, execution tests). Do NOT use when you need to validate or calibrate the judge — use validate-evaluator instead.
validate-evaluator
Calibrate an LLM judge against human labels using data splits, TPR/TNR, and bias correction. Use after writing a judge prompt (write-judge-prompt) when you need to verify alignment before trusting its outputs. Do NOT use for code-based evaluators (those are deterministic; test with standard unit tests).
generate-synthetic-data
Create diverse synthetic test inputs for LLM pipeline evaluation using dimension-based tuple generation. Use when bootstrapping an eval dataset, when real user data is sparse, or when stress-testing specific failure hypotheses. Do NOT use when you already have 100+ representative real traces (use stratified sampling instead), or when the task is collecting production logs.
evaluate-rag
Guides evaluation of RAG pipeline retrieval and generation quality. Use when evaluating a retrieval-augmented generation system, measuring retrieval quality, assessing generation faithfulness or relevance, generating synthetic QA pairs for retrieval testing, or optimizing chunking strategies.
eval-audit
Audit an LLM eval pipeline and surface problems: missing error analysis, unvalidated judges, vanity metrics, etc. Use when inheriting an eval system, when unsure whether evals are trustworthy, or as a starting point when no eval infrastructure exists. Do NOT use when the goal is to build a new evaluator from scratch (use error-analysis, write-judge-prompt, or validate-evaluator instead).
error-analysis
Help the user systematically identify and categorize failure modes in an LLM pipeline by reading traces. Use when starting a new eval project, after significant pipeline changes (new features, model switches, prompt rewrites), when production metrics drop, or after incidents.
build-review-interface
Build a custom browser-based annotation interface tailored to your data for reviewing LLM traces and collecting structured feedback. Use when you need to build an annotation tool, review traces, or collect human labels.