القائمة
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/Aditya232-rtx/Ouroboros --skill kanban-video-orchestratorيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
Add security scanning to CI/CD with Fang — GitHub Actions, GitLab CI, or any pipeline — so every pull request gets a diff-scoped AI pentest that blocks vulnerable code before it merges, with results as PR comments and SARIF uploaded to code scanning. Covers both the self-hosted open-source CLI (runs in your runner) and the managed app.fang.ai platform (GitHub/GitLab app or API, no runner infra). Use when the user asks to add security scanning, SAST/DAST, pentesting, vulnerability checks, or automated security review to their CI pipeline, pre-merge gate, or PR workflow.
Fix security vulnerabilities found by a Fang pentest (open-source CLI or app.fang.ai cloud) — triage by severity, patch the root cause rather than the symptom, and re-run Fang to prove each fix actually closes the exploit. Handles injection, XSS, SSRF, broken access control, IDOR, and other validated findings. Use after a Fang scan reports findings, or when the user asks to remediate, patch, or fix security issues from a fang_runs report, vulnerabilities.json, findings.sarif, or a cloud scan.
Run a managed pentest of a web app or API through the app.fang.ai REST API — no local Docker, LLM key, or install needed. Create an API token, register domain/repository assets, launch and poll scans, triage vulnerabilities, export SARIF, download PDF/DOCX pentest reports for SOC 2 and other compliance evidence (Enterprise plan), start PR reviews, and set up schedules and webhooks. Use when the user wants continuous or scheduled pentesting-as-a-service, an auditor-ready pentest report, scans tracked in a team dashboard, or security testing from a sandboxed agent/CI environment with no infrastructure.
عرض SKILL.md
| name | kanban-video-orchestrator |
| description | Plan and run multi-agent video production pipelines. |
| version | 1.0.0 |
| author | ["SHL0MS","alt-glitch"] |
| license | MIT |
| platforms | ["linux","macos","windows"] |
| metadata | {"hermes":{"tags":["video","kanban","multi-agent","orchestration","production-pipeline"],"related_skills":["ascii-video","manim-video","p5js","comfyui","touchdesigner-mcp","pixel-art","ascii-art","songwriting-and-ai-music","heartmula","songsee","youtube-content","claude-design","excalidraw","architecture-diagram","concept-diagrams","baoyu-comic","baoyu-infographic","humanizer","gif-search","meme-generation"],"credits":"The single-project workspace layout, profile-config patching pattern,\nSOUL.md-per-profile model, TEAM.md task-graph convention, and\n`--workspace dir:/abs/path` discipline are adapted from alt-glitch's\noriginal multi-agent video pipeline at\nhttps://github.com/NousResearch/kanban-video-pipeline.\n"}} |
Wrap any video request — from a 15-second product teaser to a 5-minute narrative short to a music video to an ASCII loop — in a Ouro Kanban pipeline that decomposes the work to specialized agent profiles.
This skill does not render anything itself. It is a meta-pipeline that:
The actual rendering happens inside the kanban once it's running, via whichever
existing skills + tools fit the scenes — ascii-video, manim-video, p5js,
comfyui, touchdesigner-mcp, songwriting-and-ai-music,
heartmula, external APIs, or plain Python with PIL + ffmpeg.
ascii-art, gifs, meme-generation, songwriting-and-ai-music).ascii-video).DISCOVER → BRIEF → TEAM DESIGN → SETUP → EXECUTE → MONITOR
The discovery process is adaptive: ask only what is actually needed. Always start with three questions to identify the broad shape:
From the answer, classify the style category. The style determines which follow-up questions to ask. Ask 2-4 at a time, listen, then proceed. Make reasonable assumptions whenever the user implies an answer.
For complete intake patterns and per-style question banks, see references/intake.md.
Once enough is known, produce a structured brief.md using the template in
assets/brief.md.tmpl. Stages:
Show the brief to the user for confirmation before designing the team. The brief is the contract — every downstream task references it.
Pick role archetypes from the library that fit this video. Compose, don't clone. Most videos need 4-7 profiles. The director is always present; the rest are picked by what the brief actually requires.
For the role library and per-style team compositions, see references/role-archetypes.md.
For mapping role → which Ouro skills + toolsets it loads, see references/tool-matrix.md.
Generate a setup script (setup.sh) and run it. The script:
~/projects/video-pipeline/<slug>/)taste/, audio/, assets/ouro profile create --cloneSOUL.md (personality + role definition)brief.md, TEAM.md, and taste/ contentouro kanban create task assigned to the directorUse scripts/bootstrap_pipeline.py to generate setup.sh from a brief +
team-design JSON. See references/kanban-setup.md
for the setup script structure, profile config patterns, and the critical
"shared workspace" rule.
Run setup.sh. Then provide the user with monitoring commands:
ouro kanban watch --tenant <project-tenant> # live events
ouro kanban list --tenant <project-tenant> # board snapshot
ouro dashboard # visual board UI
The director profile takes over from here, decomposing the work and routing tasks to specialist profiles via the kanban toolset.
Stay engaged — the kanban runs autonomously but a stuck task or bad output needs human (or AI) judgment.
Monitoring patterns: poll kanban list periodically, inspect any RUNNING task
that exceeds its expected duration with kanban show <id>, and check
heartbeats. When a worker's output fails review, the standard interventions are:
kanban_comment)For diagnostic patterns, intervention recipes, and the "task is stuck" playbook, see references/monitoring.md.
Six concrete pipelines covering very different video styles — narrative film, product/marketing, music video, math/algorithm explainer, ASCII video, real-time installation — showing how the same workflow yields very different teams and task graphs. See references/examples.md.
Discovery before action. Never start generating a brief or team without asking at least the three baseline questions. A bad brief cascades through the entire pipeline.
Match the team to the video. Don't reuse the same 4-profile setup for
every job. A music video that doesn't have a beat-analysis profile will
misfire. A narrative film that doesn't have a writer profile will produce
incoherent scenes. See references/role-archetypes.md.
One workspace per project. All profiles for a given video share the same
dir: workspace. Tasks pass artifacts via shared filesystem and structured
handoffs. Every kanban_create call passes
workspace_kind="dir" + workspace_path="<absolute project path>".
Tenant every project. Use a project-specific tenant
(--tenant <project-slug>). Keeps the dashboard scoped and prevents
cross-pollination with other ongoing kanbans.
Respect existing skills. When a scene fits an existing skill, the
relevant renderer should load that skill via --skill <name> on its task
or always_load in its profile. Do not re-derive what a skill already
provides.
The director never executes. Even with the full kanban + terminal + file toolset, the director's SOUL.md rules forbid it from executing
work itself. It decomposes and routes only — every concrete task becomes
a ouro kanban create call to a specialist profile. The kanban
orchestration guidance auto-injected into every kanban worker's system
prompt spells this out further.
Don't over-decompose. A 30-second product video does NOT need 20 tasks. Aim for the smallest task graph that still parallelizes well and exposes the right human-review gates.
Verify API keys BEFORE firing. External APIs (TTS, image-gen,
image-to-video) need keys in ${OURO_HOME:-~/.ouro}/.env or the user's secret store.
A worker that hits a missing-key error wastes a task slot. The setup
script's check_key helper aborts cleanly if a required key is missing.
SKILL.md ← this file (workflow + rules)
references/
intake.md ← discovery question banks per style
role-archetypes.md ← role library (writer, designer, animator, …)
tool-matrix.md ← skill + toolset mapping per role
kanban-setup.md ← setup script structure & profile config
monitoring.md ← watch + intervene patterns
examples.md ← six worked pipelines
assets/
brief.md.tmpl ← brief skeleton
setup.sh.tmpl ← setup script skeleton
soul.md.tmpl ← profile personality skeleton
scripts/
bootstrap_pipeline.py ← generate setup.sh from brief + team JSON
monitor.py ← polling + intervention helpers