footage-redaction

footage-redaction is a skill for Claude Code, Codex from BlackBeltTechnology/pi-agent-dashboard. It costs 83 tokens per session (1,050 once invoked), scanned A, original, MIT.

A video-processing tool that permanently applies specified crops, logo removal, and timed blurring to a recording. It can blur an area only while a detected screen element is visible, then checks the result with contact sheets, which are grids of video frames.

In plain words
What is it for?
Use it to trim and crop footage, hide email addresses, IP addresses, URLs, or watermarks, blur changing interface elements, and adjust speed or frame rate.
Why use it?
It helps remove private information, logos, or unwanted screen areas before a clip is shared. Baking the changes into the output means the redaction is part of the exported video.

Skill for Claude CodeCodex

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

Good fit Use it to trim and crop footage, hide email addresses, IP addresses, URLs, or watermarks, blur changing interface elements, and adjust speed or frame rate.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/blackbelttechnology/pi-agent-dashboard/footage-redaction
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 BlackBeltTechnology/pi-agent-dashboard --skill footage-redaction
Clone the repo
git clone --depth 1 https://github.com/BlackBeltTechnology/pi-agent-dashboard

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 footage-redaction

README.md
[![agentmods](https://agentmods.dev/badge/skills/blackbelttechnology/pi-agent-dashboard/footage-redaction/github.svg)](https://agentmods.dev/skills/blackbelttechnology/pi-agent-dashboard/footage-redaction)
Your own site
<a href="https://agentmods.dev/skills/blackbelttechnology/pi-agent-dashboard/footage-redaction"><img src="https://agentmods.dev/badge/skills/blackbelttechnology/pi-agent-dashboard/footage-redaction/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 footage-redaction

Your own site · 80×15
<a href="https://agentmods.dev/skills/blackbelttechnology/pi-agent-dashboard/footage-redaction"><img src="https://agentmods.dev/badge/skills/blackbelttechnology/pi-agent-dashboard/footage-redaction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,050 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.
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 $0.00083 $0.01050
Opus 5.5 $0.00033 $0.00420
Sonnet 5.5 $0.00017 $0.00210
Haiku 4.5 $0.00008 $0.00105

Measured 19d ago against content hash a869f08465a5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

footage-redaction 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 19d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/redact.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

packages/video-production/.pi/skills/footage-redaction/SKILL.md · 75 lines

How it starts

The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.

footage-redaction

scripts/redact.py cuts one clip and bakes its redaction in a single ffmpeg pass. It needs only Python 3 (standard library) and ffmpeg/ffprobe — no venv.

Spec

{
  "trim":  {"from": 47.0, "to": 59.0},
  "speed": 1.0,
  "fps":   30,
  "crop":  {"top": 125, "bottom": 90, "left": 0, "right": 0},
  "delogo": [{"x": 750, "y": 410, "w": 640, "h": 110, "from": 0, "to": 46.9}],
  "blur_when": [{"x": 836, "y": 338, "w": 180, "h": 56, "pad_s": 0.25,
                 "detect": {"x": 820, "y": 300, "w": 220, "h": 30,
                            "rgb": [20, 40, 90], "tol": 30, "min_ratio": 0.6}}]
}
  • Coordinate rule — every box (delogo, blur_when target and detect) is in SOURCE-frame pixels, before crop and scale, and every time is on the UNTRIMMED source timeline. Measure boxes on a full-resolution source frame; never on a cropped clip.
  • Filter order: trim → delogo → blur → crop → speed → fps → encode.
  • blur_when: the detect box is sampled every 0.25 s; it is active when at least min_ratio of its pixels are within tol of rgb (e.g. a popup's navy header). Active samples merge into windows padded by pad_s; the blur runs only inside them. Keep the detect box small (a thin strip of the popup header or status bar): detection is pure Python and its cost grows with box area × clip length.
  • Validation rejects a bad spec before writing anything, naming the field (blur_when[0].detect.min_ratio, delogo[0] …).

Run

python3 scripts/redact.py src.mov clips/c05.mp4 --spec c05.redact.json --dry-run   # windows + filter graph
python3 scripts/redact.py src.mov clips/c05.mp4 --spec c05.redact.json [--crf 16] [--strict]

--dry-run prints the resolved windows and graph and writes nothing — iterate on the spec with it. A detector that never fires prints a warning; --strict makes it an error. Output is written to <out>.partial and renamed only on success.

Per-clip caller loop

Keep the project's own shot table (clip id, source, in/out, speed, redaction spec) in the project, and call redact.py once per clip:

Read the full file on GitHub · 75 lines

Files

What ships with it

1 file 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.

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. 19d ago First seen · 75 lines · 83 tokens per session scan A a869f08465a5

Subscribe to this mod's changes

footage-redaction is a skill published in the GitHub repository BlackBeltTechnology/pi-agent-dashboard (319 stars, last pushed yesterday), licensed MIT. It adds 83 tokens to every session and 1,050 once invoked, about $0.0003 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 2026-09-27.