start

A workflow tool for starting a new pull request by creating a feature branch that follows the project's naming rules. A feature branch is a separate line of development for one change.

In plain words
What is it for?
Use it to begin feature work, create ticket-based branches, fetch issue details, and prepare the context for opening a pull request.
Why use it?
It avoids inconsistent branch names and can connect the branch to a ticket from an issue tracker. It also stores context for later workflow steps.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/rlajous/claude-code-commands/start
Any agent
npx skills add rlajous/claude-code-commands --skill start
Clone the repo
git clone --depth 1 https://github.com/rlajous/claude-code-commands

Made for: Claude Code, Codex.

Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,186 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00014 $0.02186
Opus 5 $0.00007 $0.01093
Sonnet 5 $0.00003 $0.00437
Haiku 4.5 $0.00001 $0.00219

Measured 2d ago against content hash be5db5cca41a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

start scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/start/SKILL.md · 314 lines

How it starts

The opening of the file, as written. The whole thing — 314 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Cross-runtime: follow runtime compatibility for invocation, delegation, configuration precedence, state paths, and permissions.

You are helping create a new pull request. Your task is to create a properly named feature branch, optionally fetch ticket details, and store context for subsequent commands.

Step 1: Load Configuration

Resolve project configuration with canonical-first precedence:

if [ -f ".git-workflow/config.yaml" ]; then
  CONFIG_PATH=".git-workflow/config.yaml"
elif [ -f ".claude/config.yaml" ]; then
  CONFIG_PATH=".claude/config.yaml" # legacy read-only fallback
else
  CONFIG_PATH=""
fi

Configuration Priority:

  1. .git-workflow/config.yaml (if exists)
  2. .claude/config.yaml (legacy read-only fallback)
  3. Auto-detection (package.json, pyproject.toml, etc.)
  4. Sensible defaults

Default Values (when no config):

workflow:
  type: staging
  developmentBranch: staging
  productionBranch: main
branches:
  feature: "{type}/{ticket}-{description}"
commits:
  types: [Feature, Fix, Hotfix, Refactor, Docs, Test, Chore]
  requireTicket: false
  ticketPattern: "^[A-Z]+-\\d+$"
issueTracker:
  type: auto

Step 2: Gather Information

Ask the user for the following information (use the active host user-input mechanism):

Question 1: Ticket ID

Question: "What is the ticket ID or URL?"

  • Examples:
    • PROJ-1234 (Jira format)
    • ENG-456 (Linear format)
    • #789 (GitHub issue)
    • https://linear.app/team/issue/ENG-456/...
    • https://your-org.atlassian.net/browse/PROJ-1234

Parsing Logic:

  • Extract ticket ID from URL if provided
  • Linear: Pattern /issue/([A-Z]+-\d+)/
  • Jira: Pattern /browse/([A-Z]+-\d+)
  • GitHub: Pattern issues/(\d+) or #(\d+)

Validation:

  • If commits.requireTicket: true in config, ticket is required
  • Validate against commits.ticketPattern if provided
  • If no ticket provided and not required, proceed without it

Question 2: Change Type

Read the full file on GitHub · 314 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 314 lines · 14 tokens per session scan A be5db5cca41a

Subscribe to this mod's changes

start is a skill published in the GitHub repository rlajous/claude-code-commands (30 stars, last pushed 3d ago), licensed MIT. It adds 14 tokens to every session and 2,186 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens