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 mupozg823/timecode-agent --skill skillgit clone --depth 1 https://github.com/mupozg823/timecode-agentWrote 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/mupozg823/timecode-agent/skill)<a href="https://agentmods.dev/skills/mupozg823/timecode-agent/skill"><img src="https://agentmods.dev/badge/skills/mupozg823/timecode-agent/skill/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/mupozg823/timecode-agent/skill"><img src="https://agentmods.dev/badge/skills/mupozg823/timecode-agent/skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00113 | $0.03469 |
| Opus 5.5 | $0.00045 | $0.01388 |
| Sonnet 5.5 | $0.00023 | $0.00694 |
| Haiku 4.5 | $0.00011 | $0.00347 |
Grade A, and why
timecode-agent 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 2mo 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TIMECODE-AGENT
Hypothesize from the transcript first, verify only the uncertain moments visually, then persist the result as checkpoints. Never capture every frame; state the hypothesis each capture tests. Never promote a device- or dataset-local number into a universal rule.
References, read only when needed
| Situation | Reference |
|---|---|
| OCR, diarization, faces, scene false positives, precise visual checks | Verification toolbox |
| Highlight scoring, boundaries, beat-sync rhythm cut, montage grammar, reframe, NLE handoff | Output handoff |
| Resume, search, glossary, wiki, storage | Corpus lifecycle |
| Wiki labels, relations, narrative, queries | Wiki schema |
| Ingesting 3 or more videos | Batch contract |
| Harnesses other than Claude Code | Harness matrix |
| Install, backends, profiles, cache | Runtime setup |
Request to loop routing
Fold the user's words into a loop first. Step numbers come after.
| User says | Loop | Entry |
|---|---|---|
| new video, understand, analyze, "what is this" | Ingest (develop) then Kubrick (understand) | step 0: va ingest --signals, then va brief |
| highlight, shorts, "cut this" | Kubrick, then the cut workflow of Kuleshov (edit) | named span self-converges (step 4); open-ended waits for global convergence |
| "where was that scene", recall | Search | va search — never re-ingest |
| Premiere, editor handoff, markers | Bridge | va export in step 5 |
| listing, wiki, browser, external vault refresh | Archive (project knowledge) | va index, va wiki, va view, va bridge |
Pipeline: ingest (develop), search (recall), Kubrick (understand), Kuleshov (edit), cut (assemble), archive (preserve).
Kubrick writes the fact ledger (checkpoints.jsonl); Kuleshov writes the edit
decision ledger (sequences.jsonl). Kuleshov never modifies the fact
ledger. Correct a factual error in the checkpoint, then derive the edit again.
What ships with it
8 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.
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.
- 2mo ago First seen · 285 lines · 113 tokens per session scan A 5490a94fd28c
timecode-agent is a skill published in the GitHub repository mupozg823/timecode-agent (52 stars, last pushed 3mo ago), licensed MIT. It adds 113 tokens to every session and 3,469 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 2026-08-30.
timecode-agent compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| timecode-agentmupozg823/timecode-agent | Skill | 52 | 3mo ago | MIT | A | 113 | Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |