gf-label-stats

gf-label-stats is a skill for Claude Code, Codex from byx-darwin/gitflow-cli. It costs 60 tokens per session (1,352 once invoked), scanned A, original, MIT.

A read-only report that groups project Issues by label, shows priority distribution, and identifies Issues without labels. Issues are tracked work items such as bugs or feature requests.

In plain words
What is it for?
Use it for label health checks, backlog grooming, triage planning, and finding unclassified Issues through the gf command-line tool.
Why use it?
It replaces manual counting and makes gaps in backlog classification easier to spot without changing project data.

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/byx-darwin/gitflow-cli/gf-label-stats
Any agent
npx skills add byx-darwin/gitflow-cli --skill gf-label-stats
Clone the repo
git clone --depth 1 https://github.com/byx-darwin/gitflow-cli

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for gf-label-stats

README.md
[![agentmods](https://agentmods.dev/badge/skills/byx-darwin/gitflow-cli/gf-label-stats.svg)](https://agentmods.dev/skills/byx-darwin/gitflow-cli/gf-label-stats)
Your own site
<a href="https://agentmods.dev/skills/byx-darwin/gitflow-cli/gf-label-stats"><img src="https://agentmods.dev/badge/skills/byx-darwin/gitflow-cli/gf-label-stats.svg" alt="Measured on agentmods" height="20"></a>
Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,352 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 $0.00060 $0.01352
Opus 5 $0.00030 $0.00676
Sonnet 5 $0.00012 $0.00270
Haiku 4.5 $0.00006 $0.00135

Measured 3d ago against content hash 12493549b18c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gf-label-stats 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 3d 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/gf-label-stats/SKILL.md · 152 lines

How it starts

The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.

gf-label-stats

Read-only label analytics. Queries gf label list, then gf issue list --label per label and per priority. Produces a unified report: label group counts, priority distribution with health indicators, and unclassified Issue identification. Propose fixes — never mutate.

See full label taxonomy for canonical label category reference.

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

  • gf installed: command -v gf
  • gf authenticated: gf auth status

When to Use

English 中文 Context
show label statistics 显示标签统计 health check
label distribution 标签分布 backlog grooming
unclassified issues 未分类 Issue triage backlog
triage all unclassified 对所有未分类 triage NOTgf-issue-triage
delete unused label 删除无用标签 NOT — read-only skill
modify issue labels 修改标签 NOTgf-issue-triage

When NOT to Use

Scenario Why Not Use Instead
Applying labels to Issues This skill is strictly read-only analytics /gf-issue-triage for batch Issue classification and labeling
Creating or editing label definitions This skill reads label data, not manages label metadata /gf-label-milestone for label/milestone CRUD
Analyzing a single Issue's requirements This skill analyzes label distribution across all Issues /gf-issue-review for individual Issue requirement review
Deleting unused labels This skill never mutates labels or Issues /gf-label-milestone for label deletion
Estimating Issue counts This skill uses exact CLI output only, never estimates Run gf issue list --label directly for counts

Read the full file on GitHub · 152 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. 3d ago First seen · 152 lines · 60 tokens per session scan A 12493549b18c

Subscribe to this mod's changes

gf-label-stats is a skill published in the GitHub repository byx-darwin/gitflow-cli (2 stars, last pushed 3d ago), licensed MIT. It adds 60 tokens to every session and 1,352 once invoked, about $0.0003 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.

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