Content
81%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A highly actionable, well-sequenced skill body with executable commands, an explicit visual-checkpoint feedback loop, and clean one-level-deep reference structure. The main weakness is token efficiency: overlapping context-analysis sections and a duplicated, time-sensitive pricing table that restate content already delegated to referenced files.
Suggestions
Consolidate the 'Regra Default' and 'Modelos fal.ai' pricing tables into a single model-selection table, keeping only the default rule and decision tree inline since the canonical pricing source is already delegated to models/image-models.json and docs/skill-guides/image-generator-models.md.
Merge the overlapping 'Entradas Esperadas', 'Saidas Esperadas', 'Responsabilidades', and 'Checklist Antes de Gerar' sections, which restate the same 'analyze existing visual context first' requirement four times, into one concise context-analysis workflow.
Move the dated pricing snapshot ("atualizado 2026-05") out of SKILL.md into the referenced model-docs file, keeping only the fal.ai/pricing link and a pointer, so time-sensitive data lives where it is maintained.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense with kit-specific, non-obvious content (no beginner-concept padding), but pricing data is duplicated between the "Regra Default" table and the "Modelos fal.ai" table, and five sections (Entradas/Saidas/Responsabilidades/Checklist/Analise de Contexto) repeatedly restate 'analyze existing visual context first'. A time-sensitive snapshot ("atualizado 2026-05" pricing) is inlined despite the declared canonical source being the referenced models JSON and docs file, which the guidelines penalize. Not a 2 because almost every section carries real project-specific decisions rather than generic filler. | 3 / 5 |
Actionability | Four copy-paste-ready commands cover the common cases (t2i with --prompt/--aspect/--out, edit via --ref auto-detection, --model override, --list), auth env vars are named (FAL_AI_API_KEY with fallbacks), and the adapter contract is specified as a concrete interface signature. Matches the fully-executable anchor with no material gaps. | 5 / 5 |
Workflow Clarity | The workflow is clearly sequenced with explicit validation: ordered context-analysis steps (1-5), a pre-generation checklist, a three-stage pipeline with a human validation stage, and a Checkpoint with a fix-and-retry feedback loop ("Se não corresponder, ajustar o prompt ... e regenerar. Nunca commitar um asset que não foi aberto ao menos uma vez"). Matches the anchor with feedback loops and checklists for a batch-capable process. | 5 / 5 |
Progressive Disclosure | The single bundle reference (references/generation-techniques.md, verified to exist, 182 lines, one level deep with no nested references) is clearly signaled and loaded on demand with its contents described, and detailed model schemas are delegated to a named on-demand doc. Not a 5 because the full fal.ai pricing table is inlined in SKILL.md and duplicated across two sections — content that belongs in the referenced detail file, a minor organization gap matching anchor 4. | 4 / 5 |
Total | 17 / 20 Passed |