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/gitbutlerapp/gitbutler/lite-screenshotsnpx skills add gitbutlerapp/gitbutler --skill lite-screenshotsgit clone --depth 1 https://github.com/gitbutlerapp/gitbutlerWrote 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/gitbutlerapp/gitbutler/lite-screenshots)<a href="https://agentmods.dev/skills/gitbutlerapp/gitbutler/lite-screenshots"><img src="https://agentmods.dev/badge/skills/gitbutlerapp/gitbutler/lite-screenshots.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 | $0.00079 | $0.03763 |
| Opus 5 | $0.00039 | $0.01881 |
| Sonnet 5 | $0.00016 | $0.00753 |
| Haiku 4.5 | $0.00008 | $0.00376 |
Grade A, and why
lite-screenshots scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
$ curl -s -o /dev/null -w '%{http_code}\n' \ The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 3d ago First seen · 326 lines · 79 tokens per session scan A c4a0ed98db9c
lite-screenshots is a skill published in the GitHub repository gitbutlerapp/gitbutler (21,592 stars, last pushed 3d ago), with no licence file. It adds 79 tokens to every session and 3,763 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
issue-triage
Issue triage: audit open issues, categorize, detect duplicates, cross-ref PRs, risk assessment, post comments. Args: "all" for deep analysis of all, issue numbers to focus (e.g. "42 57"), "en"/"fr" for language, no arg = audit only in French.
github-pr-workflow
Prepare a GitHub pull request from a feature branch — branch hygiene, commit shape, title/body, verification notes, screenshots for UI work, and replies to review comments.
axum-test-transport
Choose between in-process tower::ServiceExt::oneshot tests and real tokio::net::TcpListener server tests for Axum services in this repository.
issue
Use when starting a chain from a GitHub issue — turning an issue URL or number into a triaged, planned, dispatched, and reviewed pull request. Classifies the thread (bug → root-cause discipline, feature → plan chain, question → drafted reply), synthesizes a spec from the issue's own acceptance criteria, then runs the…
github-secret-hunting
Find leaked API keys, tokens, and credentials in public GitHub repositories.
engine-implementer
End-to-end phase.rs implementation pipeline: plan, review-plan, implement, review-impl, commit — each step run in a fresh spawned agent, with automatic phase decomposition for oversized workloads.