@LocalSymmetry

Creator · LocalSymmetry

Last updated · Aug 24, 2026

lofn-video

REVIEW · 56Registry indexed

Run the Lofn video/animation pipeline (steps 00–10) backed by Codex — cinematic shot lists and motion/animation prompts (Veo 3.1 formula, synchronized audio). Use for video, film, cinematic clips, animation, animated loops, motion design, or "make a video/animation with the full

OpenAgentSkill Trust Score
56/100

Do not auto-install

Quality55/100
Audit71/100
Stars22
Verified installs0

Install targets

Codex install prompt

Install the "lofn-video" agent skill from https://github.com/LocalSymmetry/lofn/tree/main/.agents/skills/lofn-video. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Run the Lofn video/animation pipeline (steps 00–10) backed by Codex — cinematic shot lists and motion/animation prompts (Veo 3.1 formula, synchronized audio). Use for video, film, cinematic clips, animation, animated loops, motion design, or "make a video/animation with the full pipeline". Covers BOTH live-cinematic and animation. Expects a Phase-0/1 orchestrator packet from the `lofn` skill; if none exists, run `lofn` first. Do NOT use for static images, music-only, story prose, or QA-only audits. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"localsymmetry-lofn-video","task":"Install lofn-video","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.

Supply asset profile

Design and creative production

Design assets, images, video, audio, multimodal media, presentation, and creative production skills.

Browse track

Scenario

Multimodal media

I need my agent to process images, video, or audio and extract useful information.

Agent fit

Claude Code + OpenAI Agents + CLI

Codex, Claude Code, Cursor, CLI, or custom agents.

Install

Ready

npx skills add LocalSymmetry/lofn --skill lofn-video

Maintenance

fresh

Pushed today

Risk

Needs review

License is unclear

GitHub quality

22

55/100 Quality · 64/100 Trust

Coverage tags

DesignMultimodal mediasecurityagent-skill

Review notes

License is unclear · Repository license is unknown; compliance is unclear.

Agent adoption scorecard

Trust, audit, and install readiness at a glance

These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.

Quality

Promising
55

Useful candidate, but compare it with alternatives before adopting.

Trust

Do not auto-install
56

Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.

Audit

Needs review
71

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

OpenAgentSkill Trust Score v5

Human review before install

Choose a stronger alternative or inspect the source manually before any install attempt.

CodexClaude CodeCursorOpenAgentSkill CLI

Stars

22 GitHub stars

Repo activity

22 stars, 1 forks

Maintenance

Pushed today

License

Unknown

Install

npx skills add LocalSymmetry/lofn --skill lofn-video

Install safety

standard package or runtime install path

Permission surface

filesystem or document access

Agent outcomes

No agent outcome data yet

Docs

Strong README/SKILL.md context

Risk summary

Review before production

  • Repository license is unknown; compliance is unclear.
  • License is unclear
  • Low GitHub adoption signal
  • Quality score needs review

Install readiness

Install path available

  • Install path is available
  • Repository evidence is available
  • License is unclear
  • No Agent Proven outcome evidence yet

Agent-readable metadata

Machine-readable decision data for this skill.

Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.

View technical data+

Suited tasks

  • Multimodal media workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Read media metadata

Suited agents

CodexClaude CodeCursorOpenAgentSkill CLIOpenAI AgentsCLI

Install decision

Command
npx skills add LocalSymmetry/lofn --skill lofn-video
Policy
review
Human review
yes

Trust and risk

Trust
56/100
Audit
71/100
Risk level
Needs review

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add LocalSymmetry/lofn --skill lofn-video

Do not use when

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • Low GitHub adoption signal
  • Repository license is unknown; compliance is unclear.
  • No OpenAgentSkill engagement data yet

Agent safety v2

55/100 · Review before install

Experimentalreview

Sparse or mixed signals. Useful for discovery, but not for autonomous installation.

Test manually in an isolated workspace and compare against safer alternatives.

Resolve via API

medium

Network access

Skill likely fetches remote pages, APIs, repositories, or external services.

medium

Filesystem access

Skill may read or write project files, documents, generated artifacts, or local workspace state.

  • License is unclear

Agent resolve plan

Let an agent verify fit before installing.

The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.

Open text plan

Agent should check

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Copy prompt

Task: Use lofn-video in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20lofn-video%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/localsymmetry-lofn-video/install
Install command: npx skills add LocalSymmetry/lofn --skill lofn-video
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent handoff

Give an agent the install path, not another directory page.

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

Open install API

Agent prompt

Use lofn-video for this task. Review https://www.openagentskill.com/api/skills/localsymmetry-lofn-video/install, then install with: npx skills add LocalSymmetry/lofn --skill lofn-video

Registry metadata

Agent-readable profile for automatic skill selection.

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open manifest

Agent fit

54/100

Multimodal media

Platforms

Claude Code, OpenAI Agents

Audit report

Needs review · 71/100

A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.

View audit reportView eval report

Agent decision cockpit

Needs validation for Multimodal media

Do a manual repository review before adding this to an agent workflow.

54
Readiness
Review
Stage

Role in stack

Needs validation

Primary fit

Multimodal media

Trust label

Needs manual review

Install path

Command ready

Use when

  • Multimodal media workflows
  • Claude Code teams
  • builders willing to evaluate younger projects

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 55/100 quality profile

review first

  • Low GitHub adoption signal
  • Repository license is unknown; compliance is unclear.
  • No OpenAgentSkill engagement data yet

Implementation path

  1. 1Install it in a sandbox agent and run one Multimodal media task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Trust profile

Do not auto-install

Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.

56
OpenAgentSkill Trust Score

GitHub adoption

FIX

22 GitHub stars

Stars/forks activity

FIX

22 stars, 1 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

Pushed today

License clarity

CHECK

Unknown

Good signals

  • AI review approved
  • Install path is available
  • Repository evidence is available
  • Recently maintained repository
  • Install command has no obvious high-risk pattern
  • Outcome loop is ready but needs first real agent run

Review before install

  • Repository license is unknown; compliance is unclear.
  • License is unclear
  • Low GitHub adoption signal
  • Quality score needs review
  • GitHub adoption: 22 GitHub stars
  • Stars/forks activity: 22 stars, 1 forks; issue activity unavailable in current metadata
  • License clarity: Unknown
  • No real agent outcome reports yet
  • Human review required before unattended installation

Recommended action

Choose a stronger alternative or inspect the source manually before any install attempt.

Quality profile

Promising candidate for agent workflows

Useful candidate, but compare it with alternatives before adopting.

55
GitHub stars
22
Freshness
Today
Install ready
Yes
License
Unknown
Review before install: Low GitHub adoption signal · Repository license is unknown; compliance is unclear.

Workflow fit

Use this skill in these scenarios

Workflow fit

Add it to a complete workflow

Alternative shortlist

Compare before you install

Similar skills that may fit this task.

Compare all

Overview

--- name: lofn-video description: Run the Lofn video/animation pipeline (steps 00–10) backed by Codex — cinematic shot lists and motion/animation prompts (Veo 3.1 formula, synchronized audio). Use for video, film, cinematic clips, animation, animated loops, motion design, or "make a video/animation with the full pipeline". Covers BOTH live-cinematic and animation. Expects a Phase-0/1 orchestrator packet from the `lofn` skill; if none exists, run `lofn` first. Do NOT use for static images, music-only, story prose, or QA-only audits. ---

# Lofn Video & Animation — Codex-backed director pipeline

> **⚖️ AUTHORITY (2026-07-01):** the `.claude/skills/` twin of this skill is the CANONICAL policy source; this Codex mirror binds to it and to `.agents/skills/lofn/EXECUTION.md` §8 (Policy Deltas — golden-output quarantine, no-skip/NON-CANONICAL, itemized packet, per-pair variation angles, judge separation, the publish bar, gate mid-bands). On any disagreement, the `.claude` file wins.

Produces cinematic shot lists and animation prompts at Lofn competition grade. This one skill covers **both** modalities the user calls "video" and "animation" — same pipeline, with the Veo 3.1 motion/audio formula and the animation archetypes layered on. Depth lives in `skills/video/` and `skills/animator/`; Codex is the engine (hybrid execution per `.agents/skills/lofn/EXECUTION.md`).

## Before you start 1. Confirm a Phase-0/1 packet exists (`core_seed.md`, `04_metaprompt.md`, `05_pair_assignments.md`, `06_director_handoff.md` with the **ICB / Panel Ledger**, filled `CREATIVE_CONTEXT.md`). **No packet → run `lofn` first.** 2. Read the motion/format craft just-in-time: - `skills/animator/SKILL.md` — Veo 3.1 prompt formula, camera language, audio direction, the 6 animation archetypes (Pulse / Morph / Orbit / Parallax / Burst / Flow), loop logic, platform optimization. - `vault/DIRECTOR_QA_DEPTH_AUDIT.md` — the Cinematic Somatic Gate + 5-element shot checklist. 3. **Mode:** *Cinematic* (multi-shot sequence / narrative clip) vs *Animation* (a single 4–8s loop/motion study). The pipeline is the same; in Animation mode each pair's variations are archetype-driven loops and you enforce loop logic (how frame 1 connects to the final frame).

## Execution (hybrid) Coordinator **00–05 inline**, then **6 pairs as parallel subagents** for 06–10. At every agent start inject the full startup packet from `EXECUTION.md` §3 — `CREATIVE_CONTEXT.md` verbatim, the handoff/assignment files, the current step contract, and the prior artifact where applicable. Default cardinality: **6 pairs × 4 = 24 shot-sets / loops → rank → top picks.**

### Coordinator steps (inline) | Step | File | Artifact | |------|------|----------| | 00 | `skills/video/steps/00_Generate_Video_Aesthetics_And_Genres.md` | `step00_aesthetics_and_genres.md` | | 01 | `skills/video/steps/01_Generate_Video_Essence_And_Facets.md` | `step01_essence_and_facets.md` | | 02 | `skills/video/steps/02_Generate_Video_Concepts.md` | `step02_concepts.md` (12 concepts) | | 03 | `skills/video/steps/03_Generate_Video_Artist_And_Critique.md` | `step03_artist_and_critique.md` | | 04 | `skills/video/steps/04_Generate_Video_Medium.md` | `step04_medium.md` | | 05 | `skills/video/steps/05_Generate_Video_Refine_Medium.md` | `step05_refine_medium.md` → **6 pairs** |

### Per-pair steps (parallel subagents, one chain per pair) | Step | File | Per-pair artifact | |------|------|-------------------| | 06 | `skills/video/steps/06_Generate_Video_Facets.md` | `pair_{NN}_step06_facets.md` | | 07 | `skills/video/steps/07_Generate_Video_Aspects_Traits.md` | `pair_{NN}_step07_aspects_traits.md` (shot guide) | | 08 | `skills/video/steps/08_Generate_Video_Generation.md` | `pair_{NN}_step08_generation.md` (4 shot-sets/loops) | | 09 | `skills/video/steps/09_Generate_Video_Artist_Refined.md` | `pair_{NN}_step09_artist_refined.md` | | 10 | `skills/video/steps/10_Generate_Video_Revision_Synthesis.md` | `pair_{NN}_step10_revision_synthesis.md` |

## The video/animation prompt contract (hard gate) Each generation prompt (step 08+) follows the Veo 3.1 formula, one element per concern:

``` [CAMERA] shot type + angle + movement (front-load this — Veo prioritizes framing) [SUBJECT] specific, not generic ("a woman in worn leather jacket, silver rings", not "a person") [ACTION] exactly what happens [SETTING] environment + time + weather/light [STYLE & AUDIO] aesthetic + explicit sound design ``` - **Separate camera from action** (each its own sentence). Describe negative space. - **Audio is directed explicitly** — Dialogue in quotes (`A woman whispers, "I remember everything."`), `SFX:` prefix, `Ambient:` soundscape, `Audio:` music. Layer ambient + SFX (+ optional music) for depth. - **Real film references** allowed for look ("Terrence Malick golden hour"); **no living-artist/actor likeness**, no real victims. - **Animation mode adds loop logic:** name the archetype (Pulse/Morph/Orbit/Parallax/Burst/Flow), set duration (4/6/8s), aspect (9:16 TikTok / 16:9 cinematic), resolution, and state how the loop closes (orbit completes 360°, pulse returns to origin, dolly reverses at midpoint, flow = landmark-free tunnel). - The 6 pairs use **distinct camera grammar / archetypes** — no two pairs default to the same move (the distinctiveness rule).

## QA & delivery Run **lofn-qa** with the **Cinematic Somatic Gate** (`vault/DIRECTOR_QA_DEPTH_AUDIT.md`, 5-element shot checklist). Rank by: opening-second hook → motion clarity → audio-image cohesion → emotional legibility → loop integrity (animation). Save each selected shot-set/loop per `skills/lofn-core/OUTPUT.md` (note intended renderer — Veo 3.1 — and aspect/duration in frontmatter); INDEX last. **Do not call render tools** — emit paste-ready prompt text; the user renders.

Technical details

Version
1.0.0
License
Unknown
Last updated
Aug 24, 2026
Published
Aug 24, 2026

Decision snapshot

Needs validation

54
Ready
Review
Stage

recent repository activity

Audit

Install review

Install and adoption review

71
Needs review
Security
74/100
Maintenance
100/100
Install
92/100
Open full auditView eval report

Agent-proven evidence

Agent-proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
Success rate
Recent failure
Outcomes
0
Output quality
Failed
0
Not relevant
0
Installs
0
Risk blocked
0
Setup needed
0
Production
0

No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.

Install

Add to agent workflow

Free and open source. Review the report before installing into production agents.

Growth loop

Share kit

X

Scenario-led draft for lofn-video, ready for a manual X post.

Curator note
lofn-video: Run the Lofn video/animation pipeline (steps 00–10) backed by Codex — cinematic shot lists an...

22 stars

https://www.openagentskill.com/skills/localsymmetry-lofn-video?ref=x
Open X draft
Optional reply with install command
Listing + install path for lofn-video:
https://www.openagentskill.com/skills/localsymmetry-lofn-video?ref=x

Install: npx skills add LocalSymmetry/lofn --skill lofn-video

Listing source

Registry indexed

Claimable

This listing was indexed from public sources and is not marked official until a maintainer claim is approved.

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Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.

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Owner claim

Claim this skill listing

This Registry indexed listing is attributed to LocalSymmetry but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.

Creator backlink kit

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Author

L

LocalSymmetry

@localsymmetry

Health signals

GitHub stars
22
Quality score
32/100
Last GitHub push
Aug 24, 2026
Framework hints
Unknown
OpenAgentSkill views
0
Install copies
0
Outbound clicks
0

Community signal

Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.

Trust & safety

Do not auto-install

56
  • GitHub adoption22 GitHub starsFIX
  • Stars/forks activity22 stars, 1 forks; issue activity unavailable in current metadataFIX
  • Recent maintenancePushed todayPASS
  • License clarityUnknownCHECK
  • README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
  • Dependency/runtime riskno major dependency risk hints in public metadataPASS