Skill audit report
Prove a converted or quantized LiteRT model on the actual device via the CompiledModel API - confirm GPU residency, compare device output against the source model, and diagnose device-only failures such as silent CPU fallback, whole-graph compile ceilings, and fp16 range breaks. Use after conversion or quantization, when device output is wrong or NaN, when a clean graph fails to compile only on device, or when GPU and CPU outputs are suspiciously identical.
Skill audit report
Prove a converted or quantized LiteRT model on the actual device via the CompiledModel API - confirm GPU residency, compare device output against the source model, and diagnose device-only failures such as silent CPU fallback, whole-graph compile ceilings, and fp16 range breaks. Use after conversion or quantization, when device output is wrong or NaN, when a clean graph fails to compile only on device, or when GPU and CPU outputs are suspiciously identical.
Skill audit report
Prove a converted or quantized LiteRT model on the actual device via the CompiledModel API - confirm GPU residency, compare device output against the source model, and diagnose device-only failures such as silent CPU fallback, whole-graph compile ceilings, and fp16 range breaks. Use after conversion or quantization, when device output is wrong or NaN, when a clean graph fails to compile only on device, or when GPU and CPU outputs are suspiciously identical.
Skill audit report
Prove a converted or quantized LiteRT model on the actual device via the CompiledModel API - confirm GPU residency, compare device output against the source model, and diagnose device-only failures such as silent CPU fallback, whole-graph compile ceilings, and fp16 range breaks. Use after conversion or quantization, when device output is wrong or NaN, when a clean graph fails to compile only on device, or when GPU and CPU outputs are suspiciously identical.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
416 GitHub stars
Stars/forks activity
INFO62
416 stars, 116 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
3d since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
INFO64
credential or environment access, network or browser surface
Install availability
PASS92
npx skills add google-ai-edge/litert-samples --skill on-device-verification
Install command safety
PASS92
standard package or runtime install path
Permission surface
WARN46
secrets or environment access, filesystem or document access
Repository evidence
PASS86
https://github.com/google-ai-edge/litert-samples/tree/main/skills/on-device-verification
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add google-ai-edge/litert-samples --skill on-device-verification
Repository
88
https://github.com/google-ai-edge/litert-samples/tree/main/skills/on-device-verification
License
86
Apache-2.0
Maintenance
100
3d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
Usable description available
Dependency risk
64
credential or environment access, network or browser surface
Install command safety
92
standard package or runtime install path
Permission surface
46
secrets or environment access, filesystem or document access
Stars/forks activity
62
416 stars, 116 forks; issue activity unavailable in current metadata
Adoption
68
416 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
416 GitHub stars
Stars/forks activity
INFO62
416 stars, 116 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
3d since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
INFO64
credential or environment access, network or browser surface
Install availability
PASS92
npx skills add google-ai-edge/litert-samples --skill on-device-verification
Install command safety
PASS92
standard package or runtime install path
Permission surface
WARN46
secrets or environment access, filesystem or document access
Repository evidence
PASS86
https://github.com/google-ai-edge/litert-samples/tree/main/skills/on-device-verification
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add google-ai-edge/litert-samples --skill on-device-verification
Repository
88
https://github.com/google-ai-edge/litert-samples/tree/main/skills/on-device-verification
License
86
Apache-2.0
Maintenance
100
3d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
Usable description available
Dependency risk
64
credential or environment access, network or browser surface
Install command safety
92
standard package or runtime install path
Permission surface
46
secrets or environment access, filesystem or document access
Stars/forks activity
62
416 stars, 116 forks; issue activity unavailable in current metadata
Adoption
68
416 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K Stars · Audit report
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OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
416 GitHub stars
Stars/forks activity
INFO62
416 stars, 116 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
3d since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
INFO64
credential or environment access, network or browser surface
Install availability
PASS92
npx skills add google-ai-edge/litert-samples --skill on-device-verification
Install command safety
PASS92
standard package or runtime install path
Permission surface
WARN46
secrets or environment access, filesystem or document access
Repository evidence
PASS86
https://github.com/google-ai-edge/litert-samples/tree/main/skills/on-device-verification
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add google-ai-edge/litert-samples --skill on-device-verification
Repository
88
https://github.com/google-ai-edge/litert-samples/tree/main/skills/on-device-verification
License
86
Apache-2.0
Maintenance
100
3d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
Usable description available
Dependency risk
64
credential or environment access, network or browser surface
Install command safety
92
standard package or runtime install path
Permission surface
46
secrets or environment access, filesystem or document access
Stars/forks activity
62
416 stars, 116 forks; issue activity unavailable in current metadata
Adoption
68
416 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
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38K Stars · Audit report
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
416 GitHub stars
Stars/forks activity
INFO62
416 stars, 116 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
3d since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
INFO64
credential or environment access, network or browser surface
Install availability
PASS92
npx skills add google-ai-edge/litert-samples --skill on-device-verification
Install command safety
PASS92
standard package or runtime install path
Permission surface
WARN46
secrets or environment access, filesystem or document access
Repository evidence
PASS86
https://github.com/google-ai-edge/litert-samples/tree/main/skills/on-device-verification
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add google-ai-edge/litert-samples --skill on-device-verification
Repository
88
https://github.com/google-ai-edge/litert-samples/tree/main/skills/on-device-verification
License
86
Apache-2.0
Maintenance
100
3d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
Usable description available
Dependency risk
64
credential or environment access, network or browser surface
Install command safety
92
standard package or runtime install path
Permission surface
46
secrets or environment access, filesystem or document access
Stars/forks activity
62
416 stars, 116 forks; issue activity unavailable in current metadata
Adoption
68
416 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
Compare nearby options
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K Stars · Audit report
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61K Stars · Audit report
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38K Stars · Audit report