Moltis is a persistent personal agent server written in Rust that runs on hardware controlled by its user. It provides an AI agent with sandboxed command execution, model-provider connections, memory, voice, scheduling, messaging integrations, browser automation, and MCP tools. Its catalogue add-ons extend the agent’s workflows and available tools.
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 skills add moltis-org/moltis --skill gifgrepgit clone --depth 1 https://github.com/moltis-org/moltisWrote 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/moltis-org/moltis/gifgrep)<a href="https://agentmods.dev/skills/moltis-org/moltis/gifgrep"><img src="https://agentmods.dev/badge/skills/moltis-org/moltis/gifgrep/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/moltis-org/moltis/gifgrep"><img src="https://agentmods.dev/badge/skills/moltis-org/moltis/gifgrep.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00021 | $0.00494 |
| Opus 5 | $0.00010 | $0.00247 |
| Sonnet 5 | $0.00004 | $0.00099 |
| Haiku 4.5 | $0.00002 | $0.00049 |
Grade A, and why
gifgrep 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 9d 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
84% identical to gifgrep — 29 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.
What it actually says
gifgrep
Use gifgrep to search GIF providers (Tenor/Giphy), browse in a TUI, download results, and extract stills or sheets.
GIF-Grab (gifgrep workflow)
- Search → preview → download → extract (still/sheet) for fast review and sharing.
Quick start
gifgrep cats --max 5gifgrep cats --format url | head -n 5gifgrep search --json cats | jq '.[0].url'gifgrep tui "office handshake"gifgrep cats --download --max 1 --format url
TUI + previews
- TUI:
gifgrep tui "query" - CLI still previews:
--thumbs(Kitty/Ghostty only; still frame)
Download + reveal
--downloadsaves to~/Downloads--revealshows the last download in Finder
Stills + sheets
gifgrep still ./clip.gif --at 1.5s -o still.pnggifgrep sheet ./clip.gif --frames 9 --cols 3 -o sheet.png- Sheets = single PNG grid of sampled frames (great for quick review, docs, PRs, chat).
- Tune:
--frames(count),--cols(grid width),--padding(spacing).
Providers
--source auto|tenor|giphyGIPHY_API_KEYrequired for--source giphyTENOR_API_KEYoptional (Tenor demo key used if unset)
Output
--jsonprints an array of results (id,title,url,preview_url,tags,width,height)--formatfor pipe-friendly fields (e.g.,url)
Environment tweaks
GIFGREP_SOFTWARE_ANIM=1to force software animationGIFGREP_CELL_ASPECT=0.5to tweak preview geometry
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.
- 9d ago First seen · 59 lines · 21 tokens per session scan A f7be07a4ff8f
gifgrep is a skill published in the GitHub repository moltis-org/moltis (2,846 stars, last pushed 6d ago), licensed MIT. It adds 21 tokens to every session and 494 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 84% identical to gifgrep, differing in 29 lines, and is treated as a copy.
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Use when captions, subtitles, or the spoken text of a YouTube video is needed — even if not explicitly requested: pasted video links or IDs, requests to read, quote, or translate a video, accessibility needs, deaf/HoH use cases, content review, or language learning. Fetches timestamped caption data from any YouTube…
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Use when video content needs to be extracted as text: pasted YouTube links or IDs, requests to transcribe, summarize, quote, translate, convert video to text, or extract information from video content. Also use when a user shares a video URL without explanation and wants to know what it says. Not for uploads or…
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rich-post
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