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Agent skill

Capturing Tui Visual Proof

by letta-ai in letta-ai/letta-code

Captures reviewable before-and-after visual proof from the real Letta Code Ink TUI.

Apache-2.0Auto-check passedDevelopment

Install Capturing Tui Visual Proof

skills CLI
$ npx skills add letta-ai/letta-code --skill capturing-tui-visual-proof -a claude-code

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

GitHub CLI
$ gh skill install letta-ai/letta-code capturing-tui-visual-proof --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/letta-ai/letta-code.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.skills/capturing-tui-visual-proof .claude/skills/capturing-tui-visual-proof && 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
capturing-tui-visual-proof
GitHub stars
3.6k
Token cost
~1.3k tokens
SKILL.md length
412 words
Files
1
Skills in repo
25
Repo updated
First seen
Licence
Apache-2.0

At a glance

Captures reviewable before-and-after visual proof from the real Letta Code Ink TUI.

  • A Letta Code PR changes interactive CLI rendering
  • SKILL.md covers Choose the Proof, Prepare Exact Before and After…, Make the Interaction… and Record with VHS, plus 2 more sections
  • Calls git, bun and gh; reaches github.com
  • Behavior and needs terminal screenshots

What it does

Capturing Tui Visual Proof is an agent skill from letta-ai/letta-code. Captures reviewable before-and-after visual proof from the real Letta Code Ink TUI. Use when a Letta Code PR changes interactive CLI rendering or behavior and needs terminal screenshots or GIFs in its PR body.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Pull requests. It works with Letta. The repository describes itself as: Stateful agents that are like people, with memory, identity, and the ability to learn and adapt. The licence is Apache-2.0.

When your agent uses it

  • A Letta Code PR changes interactive CLI rendering
  • Behavior and needs terminal screenshots
  • GIFs in its PR body

Example prompts

  • “Use the capturing-tui-visual-proof skill to capture reviewable before-and-after visual proof from the real Letta Code Ink TUI”
  • “/capturing-tui-visual-proof”

What it can do on your machine

Read from SKILL.md and the folder at commit 253a3bc. 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

    Shell commands in SKILL.md call:

    • git
    • bun
    • gh
    • ffmpeg

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

    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

Capturing Tui Visual Proof loads about 1.3k tokens when it runs. Until then it costs about 59 tokens; SKILL.md has 412 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~59
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

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 letta-ai/letta-code at commit 253a3bc, republished under its Apache-2.0 licence (© letta-ai). 412 words, ~1,307 tokens.

Download SKILL.mdSave it as .claude/skills/capturing-tui-visual-proof/SKILL.md (or your agent's skills folder).
name
capturing-tui-visual-proof
description
Captures reviewable before-and-after visual proof from the real Letta Code Ink TUI. Use when a Letta Code PR changes interactive CLI rendering or behavior and needs terminal screenshots or GIFs in its PR body.

Capturing TUI Visual Proof

Record the production TUI through bun run src/index.ts. Do not substitute a mocked Ink component, text fixture, generated image, or headless output for the real terminal workflow.

Choose the Proof

  • Static rendering change: capture before/after screenshots.
  • Interaction or state transition: capture before/after GIFs.
  • Timing or animation claim: record continuously; do not hide the interval that proves the claim.

Keep every variable except the code revision identical: terminal dimensions, theme, agent, model, prompt, fixtures, and CLI flags.

Prepare Exact Before and After Checkouts

Use the PR's base SHA rather than current main, which may have advanced:

bash
repo=$(git rev-parse --show-toplevel)
pr=1234 # replace with the PR number
base=$(gh pr view "$pr" --json baseRefOid --jq .baseRefOid)
before=/tmp/letta-code-pr-$pr-before

rm -rf "$before"
git clone --shared --no-checkout "$repo" "$before"
git -C "$before" checkout --detach "$base"

For a dependency-neutral change, reuse the current checkout's dependencies:

bash
ln -s "$repo/node_modules" "$before/node_modules"

If the PR changes dependencies, install them independently in each checkout instead. Never install through a symlinked node_modules.

Make the Interaction Deterministic

Use the same existing test agent and a new conversation for both runs. For skill-loading proof, create a small temporary project skill with a fixed reply:

bash
proof_skills=/tmp/letta-code-pr-$pr-skills
mkdir -p "$proof_skills/pr-proof-demo"
cat > "$proof_skills/pr-proof-demo/SKILL.md" <<'SKILL'
---
name: pr-proof-demo
description: Loads deterministic instructions for TUI visual proof.
---

After loading this skill, reply exactly: `Skill loaded.`
SKILL

Dry-run the flow in each checkout before recording:

bash
bun run src/index.ts \
  --agent "$AGENT_ID" \
  --new \
  --no-system-info-reminder \
  --reflection-trigger off \
  --skills "$proof_skills" \
  --skill-sources project

Do not add --model to a shared agent merely to accelerate proof; that can persistently change its model configuration.

Record with VHS

Install VHS if unavailable. Record at roughly 960px wide, 10-15 fps, and a legible font size. Produce MP4 while iterating and GIF for the PR.

Create one tape per checkout from this pattern:

text
# Replace CHECKOUT, AGENT_ID, and SKILLS_DIR before running.
Output "/tmp/pr-proof.gif"
Output "/tmp/pr-proof.mp4"
Set Shell "zsh"
Set Width 960
Set Height 720
Set FontSize 14
Set Framerate 12
Set TypingSpeed 20ms
Set Theme "Catppuccin Mocha"
Set CursorBlink false

Hide
Type "clear && cd <CHECKOUT> && bun run src/index.ts --agent <AGENT_ID> --new --no-system-info-reminder --reflection-trigger off --skills <SKILLS_DIR> --skill-sources project"
Enter
Sleep 20s
Show
Sleep 1s
Type "Use the pr-proof-demo skill, then follow its instructions."
Sleep 500ms
Enter
Sleep 1s
Hide
Sleep 45s
Show
Sleep 4s

Run it with:

bash
vhs validate /tmp/pr-proof.tape
vhs /tmp/pr-proof.tape

For a still, run the same real interaction and add Screenshot /tmp/pr-proof.png after the final state appears.

Hide may remove startup or model latency from a rendering proof while the real process continues running. First dry-run the command and choose generous waits. Never use hidden time to skip the interaction or state transition being claimed.

Before publishing, check that the recording contains no secrets, tokens, private paths, or unrelated conversation history.

Show full SKILL.md (119 more words)Show less

Inspect Every Recording

Open the GIF and inspect frames across its full duration, not just its first or last frame:

bash
mkdir -p /tmp/proof-frames
ffmpeg -y -i /tmp/pr-proof.gif -vf 'fps=1' \
  /tmp/proof-frames/frame-%02d.png

Verify that:

  • the initial, interaction, and final states are legible;
  • before reproduces the original bug;
  • after demonstrates the fix without hiding surrounding behavior;
  • both recordings use equivalent inputs and layout.

Publish to the PR

Copy only final proof assets into the branch:

bash
asset_dir=.github/pr-assets/PR-$pr
mkdir -p "$asset_dir"
cp /tmp/before.gif "$asset_dir/before.gif"
cp /tmp/after.gif "$asset_dir/after.gif"

Commit and push the assets, then embed full-SHA-pinned same-origin URLs:

bash
sha=$(git rev-parse HEAD)
git remote get-url origin
markdown
| Before | After |
| --- | --- |
| ![Before](https://github.com/OWNER/REPO/raw/FULL_SHA/.github/pr-assets/PR-NUMBER/before.gif) | ![After](https://github.com/OWNER/REPO/raw/FULL_SHA/.github/pr-assets/PR-NUMBER/after.gif) |

Use github.com/OWNER/REPO/raw/..., not raw.githubusercontent.com, and use a full commit SHA rather than a branch or short SHA. Fetch the final PR body and download both embedded URLs to confirm they return the committed files.

Keep tapes, temporary skills, MP4s, frames, and detached checkouts out of the PR.

© letta-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .skills/capturing-tui-visual-proof of letta-ai/letta-code.

Open the folder on GitHubat commit 253a3bc

Compare with similar skills

Capturing Tui Visual Proof 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.

Capturing Tui Visual Proof compared with similar skills
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Capturing Tui Visual Proof this skillletta-ai/letta-code3.6k—~1.3kAutomated safety check: PassApache-2.0
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PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Check PRonyx-dot-app/onyx32k2 repos~2.3kAutomated safety check: PassMIT
PR Design DocOpenHands/OpenHands90k—~2.4kAutomated safety check: PassMIT
WooCommerce Code Reviewwoocommerce/woocommerce11k3 repos~1.1kAutomated safety check: PassCustom licence

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Works with

Categories

Questions about Capturing Tui Visual Proof

What does Capturing Tui Visual Proof do?

Captures reviewable before-and-after visual proof from the real Letta Code Ink TUI. Capturing Tui Visual Proof is an agent skill from letta-ai/letta-code. Captures reviewable before-and-after visual proof from the real Letta Code Ink TUI.

When should I use Capturing Tui Visual Proof?

Capturing Tui Visual Proof fits situations like: A Letta Code PR changes interactive CLI rendering; behavior and needs terminal screenshots; GIFs in its PR body.

How do I install Capturing Tui Visual Proof in Claude Code?

Run `npx skills add letta-ai/letta-code --skill capturing-tui-visual-proof -a claude-code`. Or copy the skill folder (.skills/capturing-tui-visual-proof in letta-ai/letta-code) into .claude/skills/capturing-tui-visual-proof in your project. Claude Code loads it when a task matches its description.

How do I install Capturing Tui Visual Proof in Codex?

Run `npx skills add letta-ai/letta-code --skill capturing-tui-visual-proof -a codex`. Or copy the skill folder (.skills/capturing-tui-visual-proof in letta-ai/letta-code) into .agents/skills/capturing-tui-visual-proof in your project. Codex loads it when a task matches its description.

Can I use Capturing Tui Visual Proof 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 letta-ai/letta-code --skill capturing-tui-visual-proof -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/capturing-tui-visual-proof, .gemini/skills/capturing-tui-visual-proof, .github/skills/capturing-tui-visual-proof and .opencode/skills/capturing-tui-visual-proof in your project.

What does Capturing Tui Visual Proof need to run?

Going by SKILL.md and its folder, Capturing Tui Visual Proof needs the command-line tools its instructions call (git, bun, gh and ffmpeg).

Does Capturing Tui Visual Proof access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Capturing Tui Visual Proof 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 Capturing Tui Visual Proof use?

Capturing Tui Visual Proof is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Capturing Tui Visual Proof use?

About 1.3k tokens (SKILL.md is roughly 5.2k 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 Capturing Tui Visual Proof?

Skills that share tags, products or a category with Capturing Tui Visual Proof: Finishing a Development Branch (obra/superpowers, 297k stars), PR Babysitter (openinterpreter/openinterpreter, 69k stars), Check PR (onyx-dot-app/onyx, 32k stars) and PR Design Doc (OpenHands/OpenHands, 90k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Capturing Tui Visual Proof?

letta-ai (a GitHub organization) maintains it in letta-ai/letta-code, which has 3,552 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on October 9, 2026.

Source: letta-ai/letta-code on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.