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infinitetalk

自媒体创作者与内容创作者在制作数字人播报或视频配音时,只需输入单张人像与音频,即可自动生成唇形、表情、动作完美同步的无限时长说话视频。一键打造高质量虚拟主播内容,告别繁琐拍摄,让音视频创作更高效!

62

Quality

73%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./skills/infinitetalk/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

86%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 SKILL.md body is an effective, executable overview: three copy-paste-ready command examples, concrete parameter guidance, a validation-and-adjust loop for the primary mode, and clean deferral of setup/detail material to real, one-level-deep reference files. Remaining improvements are minor — consolidating the duplicated hardware notes and adding output-validation steps for the video-redubbing and TTS modes.

DimensionReasoningScore

Conciseness

The body is lean and directive — no concept explanations, just task goals, parameters, commands, and caveats. The only trimming opportunity is the duplicated hardware/weights guidance repeated between '前置准备' and '注意事项'.

4 / 5

Actionability

Three fully executable, copy-paste-ready bash commands cover the common cases (image-to-video, long-video streaming, TTS), and each script parameter is explicitly explained ('input_path', 'mode', 'size', 'sample_audio_guide_scale', 'motion_frame').

5 / 5

Workflow Clarity

Mode 1 has an explicit validation checkpoint with a feedback loop ('检查生成的视频是否同步良好... 如有异常,调整 sample_audio_guide_scale 参数'), but modes 2 and 3 list steps without any output validation, leaving minor checkpoint gaps.

4 / 5

Progressive Disclosure

The body is a well-organized overview with purpose-annotated, one-level-deep references to environment_setup.md, model_download.md, and usage_examples.md (all verified present in the bundle), plus the core script — detail is appropriately deferred to those files.

5 / 5

Total

18

/

20

Passed

Description

61%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 communicates a clear, concrete capability (portrait + audio → lip-synced unlimited-length talking video) with reasonably natural Chinese trigger terms for the digital-creator audience. Its main weaknesses are the missing explicit 'Use when...' trigger clause and marketing-style padding that crowds out coverage of the skill's full capability set.

Suggestions

Add an explicit trigger clause, e.g. 'Use when generating 数字人口播/虚拟主播 videos, doing video 配音/重配音, or when the user mentions talking-head or lip-sync video generation.'

Trim marketing phrases ('一键打造高质量', '告别繁琐拍摄', '让音视频创作更高效!') and use the reclaimed space to enumerate the other concrete capabilities: video-to-video redubbing, TTS audio generation, and low-VRAM quantization support.

Broaden trigger vocabulary with common synonyms users would actually say (talking head, lip sync, 口播视频, digital avatar) to improve retrieval.

DimensionReasoningScore

Specificity

The description names the domain (audio-driven talking video generation) and one concrete action — '只需输入单张人像与音频,即可自动生成唇形、表情、动作完美同步的无限时长说话视频' — but omits the skill's other capabilities (TTS, video redubbing, quantization) and dilutes it with marketing fluff ('一键打造高质量虚拟主播内容,告别繁琐拍摄').

3 / 5

Completeness

The 'what' is clear and concrete, but there is no explicit 'Use when...' clause — the trigger is only weakly implied by the audience framing '在制作数字人播报或视频配音时', which caps completeness at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

Natural phrases users would say are present — '数字人播报', '视频配音', '虚拟主播', '说话视频' — giving good keyword coverage; a few natural synonyms are missing (e.g. talking head, lip sync, 口播视频, file extensions).

4 / 5

Distinctiveness Conflict Risk

The audio-driven talking-head niche with digital-anchor/dubbing triggers is mostly distinct; there is minor overlap risk with generic video-generation or TTS skills.

4 / 5

Total

14

/

20

Passed

Validation

93%

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

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
anbeime/skill
Reviewed

Table of Contents

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