chat-motion-overlay

Generate configurable chat motion overlays from a transcript or screenshot, including plain bubble scenes, app-style chat containers, optional device frames, preset or uploaded avatars, nickname display rules, and transparent-video-ready Remotion bundles. Use when Codex needs to create reusable short-form chat clips for Douyin, demo videos, story reenactments, social-message proof scenes, or embeddable alpha overlays for Hyperframe and Remotion workflows.

Quality

83%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Low

Low-risk findings worth noting

Quality

Content

78%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is a well-structured, lean overview with a clear multi-step workflow and excellent progressive disclosure to real bundle files. The main weaknesses are minor: some duplicated format labels, deferred command syntax, and no explicit validation feedback loop in the render workflow.

Suggestions

Add one inline example invocation per script (e.g., 'python scripts/build_chat_overlay_spec.py transcript.txt --config config.json -o spec.json') so the workflow is copy-paste ready without opening the reference.

Insert an explicit validation checkpoint before render (e.g., 'Confirm the generated spec is valid JSON and that avatar files were copied into public/ before rendering') and a one-line failure hint.

De-duplicate the MOV/WebM delivery-format descriptions so they appear only in 'Supported Dimensions' (or only in step 5), not in both.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's competence (no explaining what Remotion or a chat overlay is), but the MOV/WebM delivery-format labels are restated in both step 5 and the 'Supported Dimensions' section, and 'Output Rules' lightly restates workflow guidance, so a few tokens could be trimmed.	4 / 5
Actionability	Concrete script paths are named at each step ('scripts/build_chat_overlay_spec.py', 'scripts/prepare_chat_overlay_bundle.py') and exact export commands are delegated to references/output-modes.md, but no inline example invocation with arguments is shown, leaving a minor gap between guidance and copy-paste readiness.	4 / 5
Workflow Clarity	A clearly numbered five-step sequence (normalize → choose config → build spec → prepare bundle → render) with per-step sub-bullets, but it lacks explicit validation checkpoints or a render-failure feedback loop; because the operation is generative rather than destructive, this is a minor rather than disqualifying gap.	4 / 5
Progressive Disclosure	The body is a concise overview that points one level deep to real, verified references (input-format.md, config-schema.md, question-strategy.md, output-modes.md), scripts, and assets/remotion-template/, with a dedicated 'Resources' section making navigation easy; the inline 'Supported Dimensions' list is a compact quick-reference while the full schema lives in config-schema.md.	5 / 5
	Total	17 / 20 Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific, complete, and distinctive, explicitly pairing a detailed 'what' with a concrete 'Use when' clause. It is held back only marginally by relying on a single verb and by leaving a few natural synonyms to the triggers field.

Suggestions

Lead with one or two additional distinct verbs (e.g., 'Generate and render configurable chat motion overlays') so the action list reads as multiple concrete actions rather than one action with a feature list.

Fold a couple of natural synonyms from the triggers field (e.g., 'animated chat' or 'chat bubbles') into the description so the most likely user phrasings appear directly in the description text.

Dimension	Reasoning	Score
Specificity	Enumerates many concrete capabilities ('plain bubble scenes, app-style chat containers, optional device frames, preset or uploaded avatars, nickname display rules, and transparent-video-ready Remotion bundles'), but they are features of a single action ('Generate') rather than multiple distinct verbs, so it stops just short of fully comprehensive action coverage.	4 / 5
Completeness	Clearly answers both what ('Generate configurable chat motion overlays from a transcript or screenshot, including...') and when ('Use when Codex needs to create reusable short-form chat clips for Douyin, demo videos, story reenactments...'), with an explicit 'Use when' clause and concrete trigger phrases; voice is third person.	5 / 5
Trigger Term Quality	Strong natural keyword coverage ('chat motion overlays', 'short-form chat clips', 'demo videos', 'story reenactments', 'alpha overlays', 'Hyperframe', 'Remotion'), with only minor gaps — simpler synonyms like 'animated chat' or 'chat bubbles' live in the triggers field rather than the description itself.	4 / 5
Distinctiveness Conflict Risk	'Chat motion overlays' is a tightly scoped niche with highly specific triggers (transparent-video Remotion bundles, Hyperframe, Douyin chat clips), making accidental activation by unrelated skills very unlikely.	5 / 5
	Total	18 / 20 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: nexu-io/open-design
Path: skills/chat-motion-overlay/SKILL.md
Commit: 1a7a23d

Reviewed: about 5 hours ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.