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/jjmartres/ai-coding-agents/glabnpx skills add jjmartres/ai-coding-agents --skill glabgit clone --depth 1 https://github.com/jjmartres/ai-coding-agentsWrote 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.
[](https://agentmods.dev/skills/jjmartres/ai-coding-agents/glab)<a href="https://agentmods.dev/skills/jjmartres/ai-coding-agents/glab"><img src="https://agentmods.dev/badge/skills/jjmartres/ai-coding-agents/glab.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00059 | $0.01472 |
| Opus 5 | $0.00030 | $0.00736 |
| Sonnet 5 | $0.00012 | $0.00294 |
| Haiku 4.5 | $0.00006 | $0.00147 |
Grade A, and why
glab 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 5d 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.
This is a copy
89% identical to glab — 75 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitLab CLI (glab) Skill
Provides guidance for using glab, the official GitLab CLI, to perform GitLab operations from the terminal.
When to Use This Skill
Invoke when the user needs to:
- Create, review, or manage merge requests
- Work with GitLab issues
- Monitor or trigger CI/CD pipelines
- Clone or manage repositories
- Perform any GitLab operation from the command line
Prerequisites
Verify glab installation before executing commands:
glab --version
If not installed, inform the user and provide platform-specific installation guidance.
Authentication Quick Start
Most glab operations require authentication:
# Interactive authentication
glab auth login
# Check authentication status
glab auth status
# For self-hosted GitLab
glab auth login --hostname gitlab.example.org
# Using environment variables
export GITLAB_TOKEN=your-token
export GITLAB_HOST=gitlab.example.org # for self-hosted
Core Workflows
Creating a Merge Request
# 1. Ensure branch is pushed
git push -u origin feature-branch
# 2. Create MR
glab mr create --title "Add feature" --description "Implements X"
# With reviewers and labels
glab mr create --title "Fix bug" --reviewer=alice,bob --label="bug,urgent"
Reviewing Merge Requests
# 1. List MRs awaiting your review
glab mr list --reviewer=@me
# 2. Checkout MR locally to test
glab mr checkout <mr-number>
# 3. After testing, approve
glab mr approve <mr-number>
# 4. Add review comments
glab mr note <mr-number> -m "Please update tests"
Managing Issues
# Create issue with labels
glab issue create --title "Bug in login" --label=bug
# Link MR to issue
glab mr create --title "Fix login" --description "Closes #<issue-number>"
# List your assigned issues
glab issue list --assignee=@me
Monitoring CI/CD
# Watch pipeline in progress
glab pipeline ci view
# Check pipeline status
glab ci status
# View logs if failed
glab ci trace
# Retry failed pipeline
glab ci retry
# Lint CI config before pushing
glab ci lint
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 233 lines · 59 tokens per session scan A a453c4863f7d
glab is a skill published in the GitHub repository jjmartres/ai-coding-agents (44 stars, last pushed 2mo ago), licensed MIT. It adds 59 tokens to every session and 1,472 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to glab, differing in 75 lines, and is treated as a copy.
Other skills, from other repositories
cocoplus-config
CocoPlus configuration SSOT — $cocoplus sync propagates cocoplus.toml into downstream artifacts; $cocoplus migrate-config converts legacy safety-config.json. Invoked via $cocoplus sync and $cocoplus migrate-config.
ship
Verify and publish by pushing, opening a PR, and watching CI; land mode merges then cleans branches. Triggers "ship it", "create PR", "/ship", "watch the PR", "babysit CI"; land mode "land it", "/ship land", "fix CI and merge".
audit-docs
Audit cross-document coherence: docs ↔ roadmap ↔ code ↔ fix index ↔ issues. Finds drift — features in docs/ not in the roadmap (or vice versa), fix-index entries already merged/closed, broken documentation-map links, dependency cycles, artifacts in the wrong language, naming-convention violations — and reports them…
audit-pr
Audit a whole PR against the delivery contract and return MERGE-READY or evidenced blockers with the full URL. Consumes the current review-change REVIEW-PASS receipt instead of re-running review axes; posts a SHA-bound ready comment; never edits or merges. Triggers: "audit-pr", "is this PR ready", "merge gate".
design-feature
Turn a raw idea or existing feature into a designed product SPEC by completing entity, integration, role, and expectation closure. Upserts never destroy recorded decisions. Triggers: "design-feature", "design this feature", "define product scope".
plan-feature-from-issue
Internal step of plan-feature: turn a feature-request issue into a scoped, sized, roadmap-mapped SPEC product half (capability closure satisfied) with Closes #N traceability.