Agent skill

Screen Demo Production

by calesthio in calesthio/generative-media-skills

Provider-independent workflow for producing terminal, IDE, documentation, browser, desktop, and application demonstration videos.

MITAuto-check passedProductivity & Automation

Install Screen Demo Production

skills CLI
$ npx skills add calesthio/generative-media-skills --skill screen-demo-production -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install calesthio/generative-media-skills screen-demo-production --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/calesthio/generative-media-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/production/content-formats/screen-demo-production .claude/skills/screen-demo-production && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
screen-demo-production
GitHub stars
197
Token cost
~3.5k tokens
SKILL.md length
1,628 words
Files
2
Skills in repo
26
Repo updated
First seen
Licence
MIT

At a glance

Provider-independent workflow for producing terminal, IDE, documentation, browser, desktop, and application demonstration videos.

  • Works in 10 steps: claim and truth classification; → exact build, account role, fixture,… → repeated workflow success and handled… → …
  • Choosing authentic capture
  • SKILL.md covers Evidence stance, Classify the truth claim, Boundaries and Build the demo contract, plus 13 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Screen Demo Production is an agent skill from calesthio/generative-media-skills. Provider-independent workflow for producing terminal, IDE, documentation, browser, desktop, and application demonstration videos. Use when choosing authentic capture, browser automation, synthetic UI, or hybrid treatment; scripting actions and narration; resetting demo state; protecting secrets and personal data; directing cursor/callouts; creating crop variants; and reviewing workflow truth, readability, accessibility, and provenance.

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `EVAL.md`).

It sits in Productivity & Automation, covering Browser automation, Text to speech and voice and Plain language and style rules. The repository describes itself as: Research-backed agent skills and tools for premium image, video, audio, voice, and generative media production across AI coding assistants. The licence is MIT.

When your agent uses it

  • Choosing authentic capture
  • Browser automation
  • Hybrid treatment
  • Scripting actions and narration

Example prompts

  • “/screen-demo-production”

Workflow steps

10 steps, taken from the first numbered list in SKILL.md.

  1. claim and truth classification;
  2. exact build, account role, fixture, mocks, clock, locale, and reset;
  3. repeated workflow success and handled failures;
  4. no PII/secrets across video, audio, trace, HAR, logs, captions, metadata, thumbnails;
  5. action-result continuity and honest timing edits;
  6. cursor/callout restraint and final-size readability;
  7. captions, visual description, contrast, and flashing;
  8. aspect variants preserve all required steps/results;
  9. codec, dimensions, fps, audio, and output integrity;
  10. provenance ledger and hashes.

What it can do on your machine

Read from SKILL.md and the folder at commit 8c85352. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • w3.org
    • playwright.dev
    • developer.mozilla.org
    • learn.microsoft.com
    • developer.apple.com
    • csrc.nist.gov
    • nist.gov
    • spec.c2pa.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Screen Demo Production loads about 3.5k tokens when it runs. Until then it costs about 116 tokens; SKILL.md has 1,628 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~116
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from calesthio/generative-media-skills at commit 8c85352, republished under its MIT licence (© calesthio). 1,628 words, ~3,454 tokens.

Download SKILL.mdSave it as .claude/skills/screen-demo-production/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
screen-demo-production
description
Provider-independent workflow for producing terminal, IDE, documentation, browser, desktop, and application demonstration videos. Use when choosing authentic capture, browser automation, synthetic UI, or hybrid treatment; scripting actions and narration; resetting demo state; protecting secrets and personal data; directing cursor/callouts; creating crop variants; and reviewing workflow truth, readability, accessibility, and provenance.

Screen demo production

Use this skill when the central evidence is an interface being operated over time: commands run, files change, controls activate, application state changes, or a workflow completes.

This is broader than SaaS marketing. It covers instructional, support, onboarding, engineering, release-note, internal-training, terminal, IDE, browser, desktop, remote-desktop, and multi-application demonstrations.

Evidence stance

  • Documented fact: behavior from official capture/automation, accessibility, privacy, or security sources.
  • Production heuristic: a practical direction choice to test with the audience and final raster.
  • Empirical observation: a result verified in the actual product/build, rehearsal, capture, or render.

Tool and OS behavior is volatile. Facts were verified 2026-07-12. Record product/build, browser/OS, automation/capture versions, fixtures, mocks, and permissions.

Classify the truth claim

Every demo must declare one:

  • Authentic capture: pixels come from the stated product or OS during an actual run.
  • Controlled authentic capture: the real UI runs with seeded data, fixed time, mocked dependencies, automation, or other material controls. Disclose them.
  • Illustrative synthetic: terminal or UI is recreated for explanation or pacing. Never describe it as a recording of a real run.
  • Hybrid: authentic pixels combined with synthetic cursor, typing, callouts, timing reconstruction, or other layers. Record each component.

Choose the least invasive mode that supports the intended claim. Synthetic UI is appropriate for conceptual or privacy-sensitive explanation; browser automation for repeatable real web flows; OS/window capture when native chrome, terminal/IDE behavior, permissions, or cross-app interaction matters.

Do not present simulated data or mocked services as proof of live performance, security, a transaction, benchmark, or customer outcome.

Boundaries

This skill owns capture-mode choice, workflow scripting, reset, privacy review, readability, cursor/callout direction, narration/caption synchronization, aspect variants, retakes, QA, and provenance.

It does not replace generic Playwright/test architecture, campaign positioning, website visual showcases without an operational workflow, general editing craft, or application accessibility conformance testing.

Build the demo contract

Define:

  • audience, task, prerequisite, expected result, and truthful claim;
  • product/build/commit, environment, account role, locale, timezone, clock, viewport, DPI/scale, theme, and feature flags;
  • authentic/controlled/synthetic/hybrid classification;
  • fixture data and reset procedure;
  • actions, readiness signals, failure branches, narration, captions, cursor, callouts, and holds;
  • do-not-show list and privacy/security approvers;
  • master and variant dimensions, duration, fps, caption/callout safe areas;
  • capture tool, codec, audio sources, and post-produced layers;
  • provenance ledger and review gates.

Use a shot ledger:

text
beat | claim | start state | action | readiness signal | result | narration | cursor/callout | hold | reset

Reset by construction

Prefer disposable directories, dedicated demo accounts, seeded fixtures, idempotent reset endpoints, fixed locale/timezone/clock, pinned dependencies, blocked notifications, and versioned mocks.

A fresh browser context isolates browser storage such as cookies and local storage, but it does not reset external database or account state. Test reset plus workflow repeatedly before recording. Every nondeterministic branch becomes an explicit branch, controlled dependency, or reason to change capture mode.

Browser automation capture

Documented facts from Playwright:

  • Browser contexts isolate session state.
  • Locator actions auto-wait for actionability such as visibility, stability, event reception, and enabled state where applicable.
  • Playwright discourages networkidle as a readiness signal and identifies fixed waitForTimeout() delays as flaky.
  • Videos are finalized when the browser context closes; viewport and video size should be explicit because default video scaling can reduce the output.
  • Stored authentication state can impersonate an account and should not be committed.
  • Traces and HAR files can contain screenshots, DOM, network, console, headers, cookies, bodies, timing, and optionally source files.

Wait for business-observable states: exact URL, response, heading, status message, enabled control, updated row, or persisted result. Separate machine readiness from viewer pacing: assert the state, then add an editorial hold.

Mock only what the truth claim permits. Disclose mocked external systems or fixed clocks. A controlled authentic UI can remain valid evidence of interface behavior, but not of the mocked provider's real response or speed.

Treat video, trace, HAR, logs, storage state, screenshots, and console output as separate sensitive artifacts. Scrubbing one does not sanitize the others.

Real screen/window capture

Browser getDisplayMedia() requires current user activation and a fresh user choice of surface; audio support varies. Operating-system capture may require permission and may display capture indicators.

For real capture:

  • select the narrowest window/surface;
  • close private apps, notifications, password managers, personal browser profiles, and unrelated terminals;
  • use a clean desktop/account and neutral wallpaper/menu bar where needed;
  • hide bookmarks, history, local paths, usernames, hostnames, API keys, tokens, email, customer data, clocks, and internal URLs;
  • test native dialogs, permissions, scaling, cursor, and audio;
  • capture handles before/after each action for editing.

Do not rely on crop or blur as the only privacy strategy. Avoid recording sensitive pixels in the first place.

Synthetic terminal and UI

Synthetic output is useful when commands/results are known, validated, privacy-sensitive, or need exact narration timing.

  • Validate commands/results in a disposable fixture when claiming they are representative.
  • Preserve exact line wrapping, prompt, width, timing, errors, and state transitions.
  • Label fixture-validated synthetic output accordingly; if not validated, label it illustrative.
  • Do not invent product capabilities, benchmark numbers, network responses, or security outcomes.
  • Keep source transcript and generation rules in provenance.

Synthetic reconstruction should improve legibility and pacing, not falsify what happened.

Direct actions, cursor, and callouts

Narrate intent before action and interpret the result afterward. Avoid speaking a changing label at the exact moment it changes.

Production heuristics:

  • park the cursor while narration carries meaning;
  • move directly, settle, click once, and leave only when needed;
  • do not circle targets continuously;
  • use one emphasis device at a time;
  • never cover the target, focus indicator, error, or result;
  • distinguish a post-produced cursor/click ring from authentic pixels in provenance;
  • hold complex results long enough to read at final size.

An automation assertion can complete faster than a viewer can comprehend. Add an editorial hold after readiness, not arbitrary sleeps before it.

Narration, captions, and visual description

Narration should explain purpose and consequence, not repeat every control label. Use exact UI names where they help task completion.

Prerecorded synchronized media with meaningful audio needs captions. Important visual-only state changes should be conveyed in narration, transcript, or audio description as required. Captions must not cover controls, errors, code, or output.

Run three tests:

  • muted: can a viewer follow actions/results through captions and visual direction?
  • audio-only: are essential outcomes described?
  • final-size: can UI, code, terminal text, callouts, and captions be read?
Show full SKILL.md (618 more words)Show less

Privacy, security, and claims

Minimize collection and capture only what serves the declared purpose. Establish access controls, retention, deletion, and reviewer responsibility for raw captures and diagnostic artifacts.

Scrub:

  • secrets, API keys, tokens, passwords, auth state, cookies, QR codes;
  • names, emails, faces, avatars, customer IDs, payments, health/HR/legal data;
  • internal hosts, paths, tickets, analytics, unreleased flags, admin controls;
  • notifications, autofill, clipboard, browser history, source maps, logs;
  • metadata and filenames as well as visible pixels.

Do not claim that a digital signature or C2PA record proves the depicted workflow occurred or that every assertion is true. Provenance can make signed records tamper-evident and record ingredients/actions.

Readability and variants

Design from the final delivery raster:

  • enlarge terminal/IDE/UI text before capture;
  • remove irrelevant panels and chrome;
  • choose viewport and device scale deliberately;
  • keep contrast and focus indicators readable;
  • zoom into evidence, then restore context;
  • avoid compression-sensitive tiny text and one-pixel lines.

Author portrait and square variants as compositions. Center-cropping desktop footage often removes navigation, labels, or result state. Re-run or recompose when the workflow does not fit.

Retakes and continuity

Retake by state-bounded beat or chapter. Save handles around transitions. Keep a take log with fixture/build, start/end state, failures, and selected take.

Editing may remove waits, but must not create impossible causal order, hide an error that changes the claim, or present a later success as the immediate result of a failed action.

QA and provenance

Verify:

  1. claim and truth classification;
  2. exact build, account role, fixture, mocks, clock, locale, and reset;
  3. repeated workflow success and handled failures;
  4. no PII/secrets across video, audio, trace, HAR, logs, captions, metadata, thumbnails;
  5. action-result continuity and honest timing edits;
  6. cursor/callout restraint and final-size readability;
  7. captions, visual description, contrast, and flashing;
  8. aspect variants preserve all required steps/results;
  9. codec, dimensions, fps, audio, and output integrity;
  10. provenance ledger and hashes.

Example 1: fixture-validated synthetic CLI

This is a complete example, not a mandatory formula.

Intent: 32-second tutorial of fictional acme deploy without showing a real shell or secrets.

Validate commands in a disposable fixture using UTC, fixed locale/terminal width, temporary home, seed demo-17, and a local fake endpoint. Save only approved output. Render synthetic terminal at 1920x1080 with large mono type and make a separate 1080x1920 layout.

text
$ acme init storefront --seed demo-17
Created storefront/acme.yaml

$ acme deploy --environment preview
Building 6 assets...
Preview ready: https://preview.example.test/storefront

$ acme status
storefront  preview  healthy  revision 8c41d2

Timeline: establish objective; type/run init; hold created-file result; deploy with deterministic progress; hold URL; run status; hold healthy state. Narration introduces intent and interprets result. Rebuild from transcript for every take and label it “synthetic terminal demonstration based on fixture-validated output.”

Likely failure: output was not actually validated. Relabel as illustrative or validate before publication.

Example 2: controlled authentic browser flow

This is a complete example, not a mandatory formula.

Intent: 45-second support training showing an operator resolving a staged order issue.

Seed a dedicated account/order/ticket through an idempotent reset. Freeze time/locale, block notifications/analytics, and disclose a mocked external shipping provider. Use a fresh context, protected auth state, and explicit 1920x1080 viewport/video size.

Wait for exact headings/statuses and response/state changes; do not use sleeps or networkidle. Rehearse with trace, then scrub/delete diagnostic artifacts and capture a clean run. A post-produced cursor settles before targets. Run reset and flow three times. QA PII, captions, console/network errors, mocked-service disclosure, final crops, and ledger of build/fixture/automation/cursor edits.

Likely failure: the success UI appears but persistence is not verified. Add an observable persisted-state assertion before the editorial hold.

Sources

Verified 2026-07-12:

© calesthio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/production/content-formats/screen-demo-production of calesthio/generative-media-skills.

  • SKILL.md
  • EVAL.md

Open the folder on GitHubat commit 8c85352

Compare with similar skills

Screen Demo Production next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Screen Demo Production compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Screen Demo Production this skillcalesthio/generative-media-skills197—~3.5kAutomated safety check: PassMIT
Tabz BrowserGGPrompts/TabzChrome147—~730Automated safety check: PassMIT
Gauntletanomalyco/browser-control440—~1.1kAutomated safety check: PassMIT
Preview Rostradpc/rostra110—~2.3kAutomated safety check: PassNone
Kuri Serverjustrach/kuri365—~6.2kAutomated safety check: NotesCustom licence
CLI Anything BrowserHKUDS/CLI-Anything52k—~1.5kAutomated safety check: WarnApache-2.0

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Questions about Screen Demo Production

What does Screen Demo Production do?

Provider-independent workflow for producing terminal, IDE, documentation, browser, desktop, and application demonstration videos. Screen Demo Production is an agent skill from calesthio/generative-media-skills. Provider-independent workflow for producing terminal, IDE, documentation, browser, desktop, and application demonstration videos.

When should I use Screen Demo Production?

Screen Demo Production fits situations like: choosing authentic capture; browser automation; hybrid treatment; scripting actions and narration.

How do I install Screen Demo Production in Claude Code?

Run `npx skills add calesthio/generative-media-skills --skill screen-demo-production -a claude-code`. Or copy the skill folder (skills/production/content-formats/screen-demo-production in calesthio/generative-media-skills) into .claude/skills/screen-demo-production in your project. Claude Code loads it when a task matches its description.

How do I install Screen Demo Production in Codex?

Run `npx skills add calesthio/generative-media-skills --skill screen-demo-production -a codex`. Or copy the skill folder (skills/production/content-formats/screen-demo-production in calesthio/generative-media-skills) into .agents/skills/screen-demo-production in your project. Codex loads it when a task matches its description.

Can I use Screen Demo Production in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add calesthio/generative-media-skills --skill screen-demo-production -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/screen-demo-production, .gemini/skills/screen-demo-production, .github/skills/screen-demo-production and .opencode/skills/screen-demo-production in your project.

What does Screen Demo Production need to run?

SKILL.md names no scripts, command-line tools or credentials: Screen Demo Production is instructions for the agent only.

Does Screen Demo Production access the network?

SKILL.md names 8 domains. As links in the text: w3.org, playwright.dev, developer.mozilla.org, learn.microsoft.com, developer.apple.com, csrc.nist.gov, nist.gov and spec.c2pa.org. This is read from the text; nothing was executed.

Is Screen Demo Production safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Screen Demo Production use?

Screen Demo Production is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Screen Demo Production use?

About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Screen Demo Production?

Skills that share tags, products or a category with Screen Demo Production: Tabz Browser (GGPrompts/TabzChrome, 147 stars), Gauntlet (anomalyco/browser-control, 440 stars), Preview Rostra (dpc/rostra, 110 stars) and Kuri Server (justrach/kuri, 365 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Screen Demo Production?

calesthio (a GitHub user) maintains it in calesthio/generative-media-skills, which has 197 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on July 14, 2026.

Source: calesthio/generative-media-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.