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inference-sh-cli

Run 150+ AI apps via inference.sh CLI (infsh) — image generation, video creation, LLMs, search, 3D, social automation. Uses the terminal tool. Triggers: inference.sh, infsh, ai apps, flux, veo, image generation, video generation, seedream, seedance, tavily

68

Quality

85%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

87%

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

A tight, highly actionable skill body with good reference structure, held back only by a thin output-parsing step in the workflow.

Suggestions

Add a concrete JSON parsing example under 'Parse the Output' (e.g., extracting the media URL field) to make the workflow's final step executable.

Show how to handle the 'MEDIA:<url>' presentation step with a short example so the loop closes on a concrete action.

DimensionReasoningScore

Conciseness

Lean and command-driven with no explanation of concepts Claude already knows; nearly every token earns its place, with only minor repetition of search examples.

3 / 3

Actionability

Provides fully executable commands with concrete app IDs (e.g., 'infsh app run falai/flux-dev-lora --input ... --json') that are copy-paste ready.

3 / 3

Workflow Clarity

The Search → Run → Parse sequence is present with pitfall handling, but the 'Parse the Output' step lacks a concrete parsing example, leaving a checkpoint gap.

2 / 3

Progressive Disclosure

A concise overview points to four real one-level-deep reference files, clearly signaled and listed in the 'Reference Docs' section for easy navigation.

3 / 3

Total

11

/

12

Passed

Description

82%

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

A specific, well-triggered description with a clear niche, weakened only by using a 'Triggers:' list instead of an explicit 'Use when...' clause for the timing guidance.

Suggestions

Add an explicit 'Use when...' clause (e.g., 'Use when the user wants to generate images, video, or run AI apps via inference.sh') so completeness can reach 3.

Lead with the use-case framing before the capability list to mirror the canonical 'what + when' structure of the good examples.

DimensionReasoningScore

Specificity

Names multiple concrete capabilities — 'image generation, video creation, LLMs, search, 3D, social automation' — matching the anchor that lists several specific actions.

3 / 3

Completeness

The 'what' is explicit, but 'when' is conveyed via a 'Triggers:' list rather than a 'Use when...' clause, which the guidelines cap at 2; it is explicit but not the canonical form.

2 / 3

Trigger Term Quality

Includes natural user-facing terms via the explicit 'Triggers:' list — 'flux, veo, image generation, video generation, seedream, seedance, tavily' — giving good coverage of what a user would actually say.

3 / 3

Distinctiveness Conflict Risk

A narrow CLI niche ('inference.sh CLI (infsh)') with distinct triggers makes it unlikely to fire for unrelated skills.

3 / 3

Total

11

/

12

Passed

Validation

81%

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

Validation13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

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

Warning

Total

13

/

16

Passed

Repository
NousResearch/hermes-agent
Reviewed

Table of Contents

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