fal-train

Train custom AI models (LoRA) on fal.ai for personalized image generation tailored to a brand, character, or style.

Quality

50%

Does it follow best practices?

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Passed

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tessl review fix ./skills/fal-train/SKILL.md

Quality

Content

40%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 body functions as a catalogue pointer rather than a self-contained skill: it is reasonably well-structured and concise, but provides almost no executable training guidance or a concrete install workflow, leaving the real action to the upstream repository.

Suggestions

Replace the pointer-only 'How to use' with at least one concrete, executable step (e.g., the actual command to clone/install the upstream bundle into the skills directory) to raise actionability.

Spell out the install workflow as a numbered sequence with the real commands and a verification step (e.g., confirm the skill appears in the agent's skill list) so workflow clarity improves and gains a checkpoint.

Trim the meta-explanation about Open Design catalogue advertising and the repeated description to tighten conciseness.

Dimension	Reasoning	Score
Conciseness	The body is short overall but carries unnecessary meta-explanation ('This catalogue entry advertises the skill in Open Design so the agent discovers it during planning') and repeats the frontmatter description, so it is mostly efficient but could be tightened rather than fully lean.	3 / 5
Actionability	The only concrete command is a trivial browser-open ('open https://github.com/fal-ai-community/skills') plus a high-level instruction to install the upstream bundle; the actual training steps are deferred to the external repo, matching 'minimal concrete guidance; high-level hints but missing the specific steps'.	2 / 5
Workflow Clarity	A rough sequence exists (inspect upstream README, install bundle, invoke by name or trigger) but the install step is hand-waved with no actual command and there are no validation checkpoints, fitting 'rough sequence present but many gaps; validation absent'.	2 / 5
Progressive Disclosure	Sections (What it does, Source, How to use) are clear and the single external reference is one level deep and clearly signaled; no bundle files exist to verify, and it is not a 5 because the content leans entirely on an external pointer rather than self-contained, well-split material.	4 / 5
	Total	11 / 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 is specific and well-targeted to a clear niche, with good natural trigger-term coverage, but it omits any explicit 'when to use' guidance, which caps completeness and limits its usefulness for skill discovery.

Suggestions

Add an explicit 'Use when...' clause (e.g., 'Use when the user wants to fine-tune a LoRA on fal.ai for brand, character, or style image generation') to lift completeness above 3.

List one or two more concrete actions (e.g., 'prepare a training image dataset, launch a fal.ai LoRA training job, and run inference with the tuned model') to raise specificity toward the multi-action anchor.

Include common synonyms such as 'fine-tune' or 'diffusion model' so trigger-term coverage reaches comprehensive.

Dimension	Reasoning	Score
Specificity	Names the domain concretely ('LoRA', 'fal.ai', 'personalized image generation') with one concrete action ('Train custom AI models'), but lists only a single action rather than several, matching the anchor for 'names domain and 1-2 concrete actions' and falling short of the multi-action anchor above.	3 / 5
Completeness	Provides a clear 'what' (train LoRA models for personalized image generation) but has no 'Use when...' clause or equivalent trigger guidance, so completeness is capped at 3 per the judging guidelines.	3 / 5
Trigger Term Quality	Includes several natural terms users would say ('train', 'custom AI models', 'LoRA', 'personalized image generation', 'brand, character, or style'), exceeding 'some relevant keywords'; it is not a 5 because common synonyms like 'fine-tune' or 'diffusion' and file extensions are absent.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche (fal.ai LoRA training for personalized image generation) with low conflict risk; it is not a 5 because overlap with general image-generation or style-transfer skills remains possible and no explicit trigger clause sharpens the boundary.	4 / 5
	Total	14 / 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/fal-train/SKILL.md
Commit: 1a7a23d

Reviewed: about 4 hours ago

Table of Contents

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