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 chrono-meta/forge-harness --skill video-ingestgit clone --depth 1 https://github.com/chrono-meta/forge-harnessWrote 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/chrono-meta/forge-harness/video-ingest)<a href="https://agentmods.dev/skills/chrono-meta/forge-harness/video-ingest"><img src="https://agentmods.dev/badge/skills/chrono-meta/forge-harness/video-ingest/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/chrono-meta/forge-harness/video-ingest"><img src="https://agentmods.dev/badge/skills/chrono-meta/forge-harness/video-ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 6 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00140 | $0.02036 |
| Opus 5 | $0.00070 | $0.01018 |
| Sonnet 5 | $0.00028 | $0.00407 |
| Haiku 4.5 | $0.00014 | $0.00204 |
Grade A, and why
video-ingest 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.
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
video-ingest — Video Content Ingestion (capability-routed)
A video carries two separable signals: the spoken transcript (text) and the visual content (on-screen demos, slides, UI). Captions give only the first. So the route is chosen by what the task needs × what engine is available × video length — not a single fixed path. This reuses frontier-digest's capability-over-engine logic and adds on-demand, need-based routing, a Claude-native frame path, output normalization, and a governance cross-check.
FH's increment over a raw video executor (sister asset claude-video, github bradautomates/claude-video;
cross-audit note in a private companion store): the executors watch; FH governs — the
governor never trusts a multimodal "comprehensive read" at face value, it cross-checks claims against the
transcript / a second pass. Same compose pattern as the other FH↔executor pairs.
Triggers
- "ingest this video" · "what does this video show / demonstrate"
- "get the transcript from this YouTube video" · "pull the captions from "
- "summarize what's on screen in this video"
- "video-ingest"
Step 0 — What does the task need? (picks the tier)
- Video understanding (visual: demos, UI walkthroughs, slides, anything not in the spoken words) → a vision path (Tier 1a or 1b below). Captions miss the screen.
- Transcript only (spoken words suffice — a talk, an interview) → go straight to yt-dlp (Tier 3); do not spend a vision engine when text is all that's needed (cost guard).
Step 1 — Capability + length probe, then tier ladder (REUSE the probe — do not re-specify)
Resolve the engine by capability, not name, via frontier-digest's Sidecar Engine Resolution
Protocol (plugins/fh-meta/skills/frontier-digest/SKILL_detail.md §Video-Harvest — single source of
the probe commands). Length is the 2nd axis (claude-video is sparse past ~10min). The ladder:
- Tier 1a — native multimodal, URL-direct (best for LONG video): an engine that watches the video and
returns spoken + visual detail, no frame cap. Verified: Gemini ingests a YouTube URL directly
(returns verbatim dialogue AND on-screen detail). Probe for a live route — the direct
geminiCLI is EOL (2026-06-18), so probeagy/ the Gemini API. Caveat (measured): a YouTube URL works, but an arbitrary (non-YouTube) stream is not reachable headless (needs file upload) — degrade for those. - Tier 1b — Claude-native frame extraction (Claude-only; SHORT/MEDIUM ≤~10min): when no external
multimodal engine is present, do not give up on visual content —
ffmpegextracts frames (auto-scaled, cap ~2fps/100 frames) → Claude's own vision via Read reads them as images (the claude-video pattern). No separate runtime, no Gemini-EOL exposure. Caution: claude-video itself is a 3rd-party executable (brew installs + optional Whisper egress) — if invoking it directly, review first; the ffmpeg+Read mechanism can also be run inline without it. - Never route video to a coding-agent CLI (codex, a non-multimodal model) — burns tokens, recovers only metadata.
- Tier 3 — yt-dlp transcript (text only; conditional — probe first, never assume):
yt-dlp --no-update --skip-download --write-auto-subs --sub-langs en \ --sub-format json3 -o "/tmp/yt_%(id)s.%(ext)s" "<URL>" python3 -c "import json,sys,re;d=json.load(open(sys.argv[1]));print(re.sub(r'\s+',' ',' '.join(s.get('utf8','') for e in d['events'] for s in e.get('segs',[]) if s.get('utf8','').strip())).strip())" /tmp/yt_<id>.en.json3--write-subs(human captions) preferred when present. Keep yt-dlp current (pip install -U yt-dlp; version/impersonation warnings are non-blocking). yt-dlp also supplies the transcript the governor cross-checks a Tier-1 visual read against. - Auth-gated (members-only / age-gated) → claude-in-chrome (operator's logged-in session).
video-ingest surfaces this route as a handoff — it does not drive the browser itself (the
mcp__claude-in-chrome__*tools are outside this skill'sallowed-tools). Caveat: needs the Anthropic "direct" plan — unavailable on a corp Bedrock laptop; surface the limit, do not loop. - Unresolvable (no vision engine, yt-dlp probe fails, not auth-fixable) → operator summary remains the path; say so plainly.
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.
- 10d ago First seen · 111 lines · 140 tokens per session scan A b09c4e6314c1
video-ingest is a skill published in the GitHub repository chrono-meta/forge-harness (14 stars, last pushed yesterday), licensed MIT. It adds 140 tokens to every session and 2,036 once invoked, about $0.0007 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.
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