Raven is an open-source agent harness for running long-term AI work with terminal execution, tracing, memory, skills, evaluation, and reusable workflows. People use the current release to operate and improve persistent AI workflows, while its described future direction is a multi-agent system that combines specialized harnesses.
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 EverMind-AI/Raven --skill git-story-filmgit clone --depth 1 https://github.com/EverMind-AI/RavenWrote 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/evermind-ai/raven/git-story-film)<a href="https://agentmods.dev/skills/evermind-ai/raven/git-story-film"><img src="https://agentmods.dev/badge/skills/evermind-ai/raven/git-story-film/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/evermind-ai/raven/git-story-film"><img src="https://agentmods.dev/badge/skills/evermind-ai/raven/git-story-film.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 | $0.00124 | $0.02958 |
| Opus 5.5 | $0.00050 | $0.01183 |
| Sonnet 5.5 | $0.00025 | $0.00592 |
| Haiku 4.5 | $0.00012 | $0.00296 |
Grade A, and why
git-story-film 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 20d 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Git story film
The user gives you a GitHub link. You direct a film of about two minutes on how that product grew up. The git history is the footage: it supplies the order, the dates and the proof. Your job is to turn it into a story a newcomer enjoys and learns from: what the product is, how it got here, what it can do for them.
Directing means you make the calls and show them, and the user approves. You own three things:
- Data. Which facts carry the film. Out of thousands of commits, pick the first commit, the release, the busiest day, the reverts and the hero feature, and put real hashes, dates and counts on screen. Everything shown is true and sourced; illustrative numbers are marked.
- Story. The protagonist, whose voice the captions are, the form the growth takes on screen, and the arc: setup (the first commit, the problem) → development (abilities arrive) → turning point (the revert, the rewrite, the busiest day) → resolution (where it landed, and what it means for the viewer).
- Look. The art style and how it changes: a look per act with a story reason, the palette, the protagonist's design, type and sound.
A mascot hatching and walking along the timeline is one form, not the only
one. The same growth can be staged as something growing in place, a machine
being built, game levels, a user's days, or a form the product suggests
(references/forms.md). Choose for each product.
The engine in engine/ (MIT, adapted from alesha-pro/tools hand-drawn-canvas-animation,
https://github.com/alesha-pro/tools/tree/main/skills/hand-drawn-canvas-animation; keep its LICENSE with
it) draws and animates, and engine/studio-ui.js turns
any film page into the review studio. examples/raven-story/ is a finished
journey film (128 s, made for EverMind's Raven, with Chinese files in zh/).
Reuse their code; do not start from a blank page.
The instructions and default examples use English. Keep dedicated Chinese film
assets in zh/ and Chinese UI labels as localization data; translating those
into English would remove the Chinese cut. Choose the output language for the
audience, and use --ui zh only for a Chinese storyboard interface.
What ships with it
35 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.
- engine/cels.js 4.9 KB runs code
- engine/core.js 81 KB runs code
- engine/LICENSE.hand-drawn-canvas-animation 1.0 KB
- engine/materials.js 3.0 KB runs code
- engine/package.json 338 B
- engine/render.mjs 7.0 KB runs code
- engine/studio-ui.js 18 KB runs code
- engine/studio.js 7.8 KB runs code
- examples/raven-story/cast-sheet.html 2.3 KB
- examples/raven-story/FONTS.md 341 B
- examples/raven-story/OUTLINE.md 8.1 KB
- examples/raven-story/raven-cast.js 23 KB runs code
- examples/raven-story/raven-flight.js 71 KB runs code
- examples/raven-story/raven-route.js 24 KB runs code
- examples/raven-story/raven-score.js 8.4 KB runs code
- examples/raven-story/raven-world.js 23 KB runs code
- examples/raven-story/raven.html 4.1 KB
- examples/raven-story/storyboard/storyboard.html 17 KB
- examples/raven-story/zh/raven-cast.js 23 KB runs code
- examples/raven-story/zh/raven-flight.js 71 KB runs code
- examples/raven-story/zh/raven-route.js 24 KB runs code
- examples/raven-story/zh/raven-world.js 23 KB runs code
- README.md 6.5 KB
- README.zh-CN.md 6.0 KB
- references/craft.md 7.0 KB
- references/directing.md 8.7 KB
- references/forms.md 6.5 KB
- references/production.md 7.0 KB
- references/story.md 6.6 KB
- references/text-and-fonts.md 4.4 KB
- scripts/fetch_fonts.sh 2.0 KB runs code
- scripts/frames.mjs 3.6 KB runs code
- scripts/git_timeline.py 3.4 KB runs code
- scripts/render-hq.mjs 4.6 KB runs code
- scripts/storyboard.py 15 KB runs code
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.
- 20d ago First seen · 180 lines · 124 tokens per session scan A 3bdc18a5d2cb
git-story-film is a skill published in the GitHub repository EverMind-AI/Raven (5,497 stars, last pushed today), licensed Apache-2.0. It adds 124 tokens to every session and 2,958 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-09-28.
Other skills, from other repositories
publish-site
Versioned site deploys to GitHub/Cloudflare/Netlify Pages.
batch
Research and plan a large-scale change, then execute it in parallel across 5–30 isolated worktree agents that each open a PR.
github
GitHub via gh CLI: PRs, issues, reviews, repos, auth.
ship-it
Pre-flight and deploy -- catch the classic day-one embarrassments (exposed keys, missing env vars, broken build, open endpoints), then ship to Vercel with domains and analytics wired. Use when the app is ready for other humans.
version-bump
Automated semantic versioning and release workflow for Claude Code plugins. Handles version increments across package.json, marketplace.json, plugin.json manifests, build verification, git tagging, GitHub releases, and changelog generation. Ends with the agent running npm publish itself using the maintainer's npm…
git
Source-control safety for Git. Two rules apply whether or not you read the body. First, never commit, amend, push, tag, rebase, cherry-pick, revert, or reset --hard unless the user asked for that exact write in this session. An explicit request to create a new commit counts anywhere in the user's own task text, but it…