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.
npx agentmods add skills/byx-darwin/gitflow-cli/gf-issue-createnpx skills add byx-darwin/gitflow-cli --skill gf-issue-creategit clone --depth 1 https://github.com/byx-darwin/gitflow-cliWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00048 | $0.01388 |
| Opus 5 | $0.00024 | $0.00694 |
| Sonnet 5 | $0.00010 | $0.00278 |
| Haiku 4.5 | $0.00005 | $0.00139 |
Grade A, and why
gf-issue-create 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.
How it starts
The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gf-issue-create
Interactive workflow that collects title, description, optional labels/assignee, then invokes gf issue create and returns the new Issue URL.
CLI Requirement
MUST use gf CLI, NOT gh CLI.
| CLI | Scope | Platform Support |
|---|---|---|
gf |
This project | GitHub + GitLab + GitCode |
gh |
GitHub only | GitHub only |
Why: gf is the unified CLI for this project. Using gh breaks GitLab/GitCode compatibility.
Preconditions
gfinstalled:command -v gfgfauthenticated:gf auth status
When to Use
| English | 中文 | Context |
|---|---|---|
| create an issue | 创建 Issue | bug / feature report |
| open an issue | 打开 Issue | new work item |
| file a bug | 上报缺陷 | corresponds to --label bug |
| new feature issue | 功能 Issue | corresponds to feat: prefix |
When NOT to Use
| Scenario | Why Not | Use Instead |
|---|---|---|
| Analyzing Issue requirement quality | This skill creates Issues, not analyzes their quality | /gf-issue-review for requirement completeness analysis |
| Batch classifying open Issues | This skill creates one Issue at a time | /gf-issue-triage for bulk classification |
| Editing existing Issue fields | This skill only creates new Issues | /gf-issue for edit/close/reopen/comment operations |
| Automated bug reporting from CLI errors | This skill requires manual input, not automated detection | /gf-autoreport-bug for automated pending.json processing |
| Viewing or listing Issues | This skill only creates, never reads existing Issues | /gf-issue for list/view/comment operations |
Core Pattern
gf auth status
gf issue create --title "<prefix>(scope): summary" --body "<md>" [--label <l>...]
Quick Reference
| Goal | Command |
|---|---|
| Create | gf issue create --title "<title>" --body "<md>" [--label <l>] [--assignee <u>] |
| Add label | append --label <label> (repeatable) |
Title prefixes: feat: fix: docs: refactor: chore: test: perf:
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.
- 2d ago First seen · 168 lines · 48 tokens per session scan A 45d1727c97db
gf-issue-create is a skill published in the GitHub repository byx-darwin/gitflow-cli (2 stars, last pushed 2d ago), licensed MIT. It adds 48 tokens to every session and 1,388 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
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.
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.
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.
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.
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…