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render-3d-product-showcase

Assemble a premium 3D product-showcase ad from a config — four beat clips (an orbiting hero rotation, a macro push-in, a physics reveal, a typographic close) normalized to the chosen backdrop colour, hard-concatenated in order, closed on a deterministic Playwright brand end card, and mixed under one instrumental bed at loudnorm I=-16 (music-only, no VO). Ships the runnable build_endcard.py + build_masters.py; the rotation/macro clips are create-video-fal i2v seeded on a create-image-fal styled hero, the reveal is Veo3 i2v, and the bed is create-music-elevenlabs. Use for the 3d-product-showcase format.

64

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

72%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.

A well-structured, operational skill body with strong progressive disclosure and mostly copy-paste-ready commands. The main gaps are the absence of explicit output-validation checkpoints in the batch assembly workflow and minor repetition of the free-cost emphasis.

Suggestions

Add an explicit validation checkpoint after build_masters.py (e.g., 'Verify: ffprobe master.mp4 — duration ≈ 15s, 720×1280, h264+aac, audio present') so the workflow has a feedback loop per the rubric's batch-operation requirement.

Replace the elided anchor-frame extraction with the full command ('ffmpeg -sseof -0.1 -i beat1.mp4 -frames:v 1 beat1_last_frame.png') so every step is copy-paste ready.

State the FREE/spends-nothing property once and cut the two repetitions ('This is the FREE, deterministic assembly stage — it spends nothing', 'cost $0') to tighten the token budget.

DimensionReasoningScore

Conciseness

The body is dense with pipeline-specific information Claude would not know (backdrop/lighting mapping, ffmpeg flags, loudnorm targets) and avoids explaining known concepts, but the FREE/spends-nothing emphasis is repeated three times ('FREE, deterministic assembly', 'This is the FREE, deterministic assembly stage — it spends nothing', 'Re-cuts reuse the existing beats and cost $0'). Efficient overall with minor trimming opportunities — anchor 4, not 5.

4 / 5

Actionability

Two copy-paste-ready commands with concrete flags ('build_endcard.py --bg beat1_last_frame.png --headline "…" --wordmark <wordmark> --out endcard.png', 'build_masters.py --config config.json --clips working/clips …') plus specific ffmpeg parameters (720×1280, 24fps, yuv420p, crf 18, loudnorm I=-16 TP=-1.5 LRA=11). Minor gaps: the Beat 1 anchor-frame extraction is elided ('ffmpeg -sseof -0.1 … -frames:v 1') and the paid beat generation is delegated to other capabilities — mostly executable, matching anchor 4.

4 / 5

Workflow Clarity

The sequence is clear (choices → beat generation → endcard → masters) with a numbered two-step run, but there are no explicit validation checkpoints — no step verifies the master (duration, resolution, audio stream) or the endcard output before shipping. Processing and concatenating four beat clips is a batch operation, so per the rubric's cap, missing validation holds this at anchor 3 ('sequence present but checkpoints missing or implicit') rather than 4.

3 / 5

Progressive Disclosure

SKILL.md is a concise overview that clearly signals one-level-deep bundle files with their roles ('scripts/PIPELINE.md maps every config block to its source step; scripts/README.md documents the assembly'), and all referenced files (config.example.json, build_endcard.py, build_masters.py, PIPELINE.md, README.md) exist in the bundle. Content is appropriately split between overview, contract, and detailed references — matches anchor 5.

5 / 5

Total

16

/

20

Passed

Description

83%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.

A strong description: concrete, comprehensive, third-person, and clearly differentiated, with only minor weaknesses in trigger phrasing. Broadening the 'when' clause beyond the internal format slug and adding a couple of natural synonyms would make it fully robust.

DimensionReasoningScore

Specificity

Enumerates multiple concrete actions — 'an orbiting hero rotation, a macro push-in, a physics reveal, a typographic close', 'normalized to the chosen backdrop colour, hard-concatenated in order', 'mixed under one instrumental bed at loudnorm I=-16' — with named runnable scripts (build_endcard.py + build_masters.py). Coverage is comprehensive and nothing is vague; it clearly exceeds the 'several specific actions, minor gaps' anchor.

5 / 5

Completeness

The 'what' is explicit and detailed (four beats, normalization, concat, end card, music mix), and a 'when' clause exists ('Use for the 3d-product-showcase format'), but the trigger references a format slug rather than concrete user-facing trigger phrases. Both present with the 'when' less explicit — matches anchor 4, not 5 (no natural trigger phrases) and not 3 (the 'when' is explicit, not merely implied).

4 / 5

Trigger Term Quality

Natural phrases like '3D product-showcase ad', 'brand end card', and 'instrumental bed' are present, but the description leans heavily on internal capability slugs (create-video-fal i2v, Veo3 i2v, create-music-elevenlabs) and omits common synonyms a user might say ('commercial', 'product video', 'render'). Good coverage with a few natural terms missing — between anchors 3 and 4, noticeably above the midpoint.

4 / 5

Distinctiveness Conflict Risk

A clear niche — assembling a specific four-beat 3D product-showcase format with named scripts and unique tool chain — makes it highly distinguishable from any other skill, with explicit boundary statements ('There is no Higgsfield / Marketing Studio in this format'). Minimal conflict risk.

5 / 5

Total

18

/

20

Passed

Validation

93%

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

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository
gooseworks-ai/goose-skills
Reviewed

Table of Contents

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