stage-assemble

stage-assemble is a skill for Claude Code, Codex from Orkas-AI/Orkas. It costs 3 tokens per session (5,235 once invoked), scanned A, original, MIT.

A guide for executing an approved video production plan into one finished file. An EDL, or edit decision list, is a recorded sequence of planned media operations.

In plain words
What is it for?
Use it to resume production, follow the signed edit list, combine video parts, mix audio, and produce the final render.
Why use it?
It prevents the assembly step from silently changing an approved plan or continuing when its approval is no longer valid.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to resume production, follow the signed edit list, combine video parts, mix audio, and produce the final render.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/orkas-ai/orkas/stage-assemble
About the project

Orkas is a desktop application for commanding a team of AI agents through one chat, with a commander model assigning work to specialist agents in parallel or in sequence. People use it to coordinate research, writing, presentations, and software tasks while keeping files on their computer. The catalogue includes skills for extending the agents available to Orkas.

Orkas-AI/Orkas · 1,848 stars · on GitHub · orkas.ai

Install

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.

Any agent
npx skills add Orkas-AI/Orkas --skill stage-assemble
Clone the repo
git clone --depth 1 https://github.com/Orkas-AI/Orkas

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for stage-assemble

README.md
[![agentmods](https://agentmods.dev/badge/skills/orkas-ai/orkas/stage-assemble/github.svg)](https://agentmods.dev/skills/orkas-ai/orkas/stage-assemble)
Your own site
<a href="https://agentmods.dev/skills/orkas-ai/orkas/stage-assemble"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/stage-assemble/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.

agentmods 80×15 button for stage-assemble

Your own site · 80×15
<a href="https://agentmods.dev/skills/orkas-ai/orkas/stage-assemble"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/stage-assemble.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 3 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,235 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 3 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 27
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
  • medium Excessive Agency · line 93
    Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.
    Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.
  • medium Excessive Agency · line 118
    Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.
    Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00003 $0.05235
Opus 5 $0.00002 $0.02618
Sonnet 5 $0.00001 $0.01047
Haiku 4.5 $0.00000 $0.00524

Measured 10d ago against content hash 8853f4c14c9c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

stage-assemble 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 10d 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.

resources/builtin/marketplace/agents/79df9cc89f5f/skills/stage-assemble/SKILL.md · 131 lines

How it starts

The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.

stage-assemble

How to execute a validated, currently authorized project/plan.json into one finished file. Start/resume with production.status; if plan_approval_current is false, pass the state to gate-control and stop instead of producing or opening child gates. Walk the signed EDL; do not re-plan. Host-neutral: VideoStudio-specific edit/plan work runs through skill scripts (stage-edit edit_video, stage-plan video_plan via bin/run-skill.cjs), while authorization state, composition, and transcription run through the required built-in video_studio runtime; generic built-in capabilities remain generate_video / generate_image / generate_speech.

Script calls used here

"$ORKAS_NODE" "$ORKAS_PC_DIR/bin/run-skill.cjs" stage-edit edit_video -- --op concat --inputs project/parts/a.mp4,project/parts/b.mp4 --output project/render/primary.mp4
"$ORKAS_NODE" "$ORKAS_PC_DIR/bin/run-skill.cjs" stage-edit edit_video -- --op mix --input project/render/primary.mp4 --audio-segments @project/audio_segments.json --output project/render/mixed.mp4
"$ORKAS_NODE" "$ORKAS_PC_DIR/bin/run-skill.cjs" stage-edit edit_video -- --op normalize_loudness --input project/render/draft.mp4 --output project/render/video.mp4

When this document says stage-edit edit_video --op ..., call the matching bin/run-skill.cjs command above with the relevant paths. For compose/transcription work, call video_studio directly. Do not call deprecated direct tools.

Step 1 — Produce each segment (delegate by source)

Iterate segments in order. For each, produce its produced_path according to source, then write that path + status:"done" back into the segment so a resume never re-produces it:

  • editstage-edit: cut the segment's input_id to its [in_sec, out_sec] window → project/cuts/<id>.mp4. Those are the EDL's field names, not flags: the command is stage-edit edit_video --op trim --input <file> --start <in_sec> --duration <out_sec - in_sec> --output project/cuts/<id>.mp4.
  • composestage-compose: the host derives this child's composition-manifest.json from the signed segment's spec.composition_plan when the plan is inherited — do not hand-author it, and author only index.html. Keep it silent: no tracks and no narration_intent (the voice is signed once on the parent EDL). Set audio.owner:"assembler" whenever any scene carries narration_text — it renders silent exactly like "none" while naming the real owner, so the host stops asking this segment for its own narration audio. Use "none" only for a segment with no narration at all. Ask gate-control to resolve parent Gate B inheritance for the owning plan/segment, then follow the returned doctor/prepare path without creating a child user gate. Continue with visual authoring, native-required inspect/snapshot, and draft to project/parts/<id>.mp4 only while the binding stays current. Run the QA phases for compose segments as ONE batched call per phase across the production rather than one call per segment: the batched path defaults its scope to the segments with no current frames, returns full findings only for the failures, and returns the production state once instead of repeating it per segment. Use a single-composition QA call only to re-check one named segment. Only compose segments need snapshot evidence, because their artifact is HTML; an edit/generate/provided segment is captured by its own produced_path file the moment that file exists, so never run a QA phase on one and never treat it as unfinished work. When every segment is captured (production.status reports no uncaptured_segment_ids), stop at the keyframe preview. The batched snapshot phase returns production_contact_sheet: ONE image of the whole video, segments in playback order, media segments included as an extracted still. Lead the stop with it — it is the artifact the user judges the video from. Then list each segment's own locators in playback order, one row per segment including the media-backed ones (a cut or generated shot has no snapshot — carry its produced_path so the user can play it), one line inviting changes, and <plan-interaction status="open" /> — no form, no per-segment approvals. Never present a per-segment contact sheet as the production preview: four links to four children is not a look at the video. Assembly starts only from the user's reply; a reply that names no change is the go-ahead, while a named change is applied without asking the user to approve their own instruction. Re-capture the resulting complete production preview and return it in the next preview message — the message that ENDS the turn. A completed turn keeps only your final message, so frames posted mid-turn were never seen by the user. Put the updated contact sheet and locators in the turn's last message itself. The stop happens once per complete production visual identity: narration/audio-only work inherits it when every visible segment stays byte-identical; changing any composed frame or media-backed segment creates a new aggregate identity and the changed whole-video preview stops once before assembly. There are still no per-segment approvals.
  • generatestage-generate (+ stage-consistency for recurring characters): proceed only while production.status reports the current paid-generation signature. Call generate_video or generate_image with production_plan_path:"project/plan.json" and production_segment_id:<id>project/assets/<id>.<ext>. When the segment has operation:"edit", treat it as the bounded semantic-edit executor for the EDIT/AUTO workflow: pass the exact original reference video and obey top-level references + edit_strategy; never widen it into regeneration. Every auxiliary portrait/keyframe is already its own signed generate segment; do not create unplanned billable calls. The host transaction reuses a completed artifact and blocks an interrupted/failed duplicate. Pass pending/failed state to gate-control; never automatically retry or invent a recovery API, and use a new output path for any later authorized retry.
  • provided → use spec.asset_id as-is (probe it first; conform aspect/fps if needed).

Read the full file on GitHub · 131 lines

Changes

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.

  1. 10d ago First seen · 131 lines · 3 tokens per session scan A 8853f4c14c9c

Subscribe to this mod's changes

stage-assemble is a skill published in the GitHub repository Orkas-AI/Orkas (1,848 stars, last pushed yesterday), licensed MIT. It adds 3 tokens to every session and 5,235 once invoked, about $0.0000 per session on Opus 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 2026-08-30.