Skill audit report
Convert a Hugging Face LLM or vision-language model checkpoint into a .litertlm bundle that runs on the LiteRT-LM runtime with verified quality - classify the architecture against known runtime walls, pick the recipe family (dense, reasoning, hybrid SSM, VLM), export, quantize, gate the result against the source model, and publish. Use when converting a new LLM or VLM to LiteRT-LM, when a converted bundle crashes on the first message or dies at engine creation, when a quantized model answers worse than its source, or when deciding whether a model is convertible at all.
Skill audit report
Convert a Hugging Face LLM or vision-language model checkpoint into a .litertlm bundle that runs on the LiteRT-LM runtime with verified quality - classify the architecture against known runtime walls, pick the recipe family (dense, reasoning, hybrid SSM, VLM), export, quantize, gate the result against the source model, and publish. Use when converting a new LLM or VLM to LiteRT-LM, when a converted bundle crashes on the first message or dies at engine creation, when a quantized model answers worse than its source, or when deciding whether a model is convertible at all.
Skill audit report
Convert a Hugging Face LLM or vision-language model checkpoint into a .litertlm bundle that runs on the LiteRT-LM runtime with verified quality - classify the architecture against known runtime walls, pick the recipe family (dense, reasoning, hybrid SSM, VLM), export, quantize, gate the result against the source model, and publish. Use when converting a new LLM or VLM to LiteRT-LM, when a converted bundle crashes on the first message or dies at engine creation, when a quantized model answers worse than its source, or when deciding whether a model is convertible at all.
Skill audit report
Convert a Hugging Face LLM or vision-language model checkpoint into a .litertlm bundle that runs on the LiteRT-LM runtime with verified quality - classify the architecture against known runtime walls, pick the recipe family (dense, reasoning, hybrid SSM, VLM), export, quantize, gate the result against the source model, and publish. Use when converting a new LLM or VLM to LiteRT-LM, when a converted bundle crashes on the first message or dies at engine creation, when a quantized model answers worse than its source, or when deciding whether a model is convertible at all.
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
2d since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
FAIL36
command execution surface, credential or environment access
Install availability
PASS92
npx skills add google-ai-edge/litert-samples --skill litert-conversion-workflow
Install command safety
PASS92
standard package or runtime install path
Permission surface
FAIL22
secrets or environment access, shell or command execution
Repository evidence
PASS86
https://github.com/google-ai-edge/litert-samples/tree/main/skills/litert-conversion-workflow
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 litert-conversion-workflow
Repository
88
https://github.com/google-ai-edge/litert-samples/tree/main/skills/litert-conversion-workflow
License
86
Apache-2.0
Maintenance
100
2d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
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
2d since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
FAIL36
command execution surface, credential or environment access
Install availability
PASS92
npx skills add google-ai-edge/litert-samples --skill litert-conversion-workflow
Install command safety
PASS92
standard package or runtime install path
Permission surface
FAIL22
secrets or environment access, shell or command execution
Repository evidence
PASS86
https://github.com/google-ai-edge/litert-samples/tree/main/skills/litert-conversion-workflow
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 litert-conversion-workflow
Repository
88
https://github.com/google-ai-edge/litert-samples/tree/main/skills/litert-conversion-workflow
License
86
Apache-2.0
Maintenance
100
2d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
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.
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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
2d since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
FAIL36
command execution surface, credential or environment access
Install availability
PASS92
npx skills add google-ai-edge/litert-samples --skill litert-conversion-workflow
Install command safety
PASS92
standard package or runtime install path
Permission surface
FAIL22
secrets or environment access, shell or command execution
Repository evidence
PASS86
https://github.com/google-ai-edge/litert-samples/tree/main/skills/litert-conversion-workflow
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 litert-conversion-workflow
Repository
88
https://github.com/google-ai-edge/litert-samples/tree/main/skills/litert-conversion-workflow
License
86
Apache-2.0
Maintenance
100
2d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
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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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
2d since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
FAIL36
command execution surface, credential or environment access
Install availability
PASS92
npx skills add google-ai-edge/litert-samples --skill litert-conversion-workflow
Install command safety
PASS92
standard package or runtime install path
Permission surface
FAIL22
secrets or environment access, shell or command execution
Repository evidence
PASS86
https://github.com/google-ai-edge/litert-samples/tree/main/skills/litert-conversion-workflow
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 litert-conversion-workflow
Repository
88
https://github.com/google-ai-edge/litert-samples/tree/main/skills/litert-conversion-workflow
License
86
Apache-2.0
Maintenance
100
2d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
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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Usable description available
Dependency risk
36
command execution surface, credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
22
secrets or environment access, shell or command execution
Stars/forks activity
62
416 stars, 116 forks; issue activity unavailable in current metadata
Adoption
68
416 GitHub stars
Financial decision safety
20
Potential execution surface detected; do not connect live broker, exchange, wallet, or payment credentials.
Usable description available
Dependency risk
36
command execution surface, credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
22
secrets or environment access, shell or command execution
Stars/forks activity
62
416 stars, 116 forks; issue activity unavailable in current metadata
Adoption
68
416 GitHub stars
Financial decision safety
20
Potential execution surface detected; do not connect live broker, exchange, wallet, or payment credentials.
Usable description available
Dependency risk
36
command execution surface, credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
22
secrets or environment access, shell or command execution
Stars/forks activity
62
416 stars, 116 forks; issue activity unavailable in current metadata
Adoption
68
416 GitHub stars
Financial decision safety
20
Potential execution surface detected; do not connect live broker, exchange, wallet, or payment credentials.
Usable description available
Dependency risk
36
command execution surface, credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
22
secrets or environment access, shell or command execution
Stars/forks activity
62
416 stars, 116 forks; issue activity unavailable in current metadata
Adoption
68
416 GitHub stars
Financial decision safety
20
Potential execution surface detected; do not connect live broker, exchange, wallet, or payment credentials.