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render-cgi-sizzle

Assemble a 3D-CGI app sizzle — nano-banana CGI plates (blank-glow floating phone + a CGI studio with rim-light + placeholder burst shapes; studio look and phone finish come from the recipe choices) plus PIL compositing of the REAL App Store screenshots onto the bezel + burst-out overlays, driven by Kling 3.0 i2v steady-float per beat with a per-beat Ken-Burns FFmpeg push-in fallback when Kling garbles the UI, then VO/music mix (sidechain duck, loudnorm) + 1.15x speed + anti-AI grain finalize. The on-screen UI, any faces in it, and the wordmark are ALWAYS real assets composited via PIL — never AI-rendered. The paid steps (plates, i2v clips, VO, music) are separate capabilities; this ships the config + PIPELINE + FREE assembly and the recipe orchestrates the spend. Use for the cgi-app-sizzle video format.

60

Quality

76%

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SecuritybySnyk

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tessl review fix ./skills/ads/capabilities/render-cgi-sizzle/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

71%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 is a well-structured overview with excellent progressive disclosure into real, verified bundle files, and the pipeline order plus fallback rules are concrete and unambiguous. Its weaknesses are structural repetition (the real-UI contract and Ken-Burns fallback each restated three times) and the absence of explicit validation steps for the FREE intermediate outputs.

Suggestions

State the real-UI/never-AI contract and the Ken-Burns fallback rule once each — keep them in the Contract section and trim their restatement from the Choices bullet list and Run section — to cut roughly a third of the body.

Add one explicit validation step per FREE stage, e.g. 'verify each scene-NN-composite.png screen sits inside the bezel before queuing the Kling beat' and 'confirm ffprobe-measured VO durations sum to ~22s before locking beat windows'.

Resolve or local-ize the dangling source-run reference in the bundle (PIPELINE.md points at 'clients/masterclass/ad-runs/run-03-run-03/working/' scripts that are not shipped) so the Run section's guidance is executable from this skill alone.

DimensionReasoningScore

Conciseness

The body explains nothing Claude already knows and assumes competence, but it restates the same points multiple times: 'The on-screen UI, any faces in it, and the wordmark are ALWAYS real assets — never AI-rendered' appears in the bullet list, again in the PIL bullet, and again as Contract item 1; the Ken-Burns fallback appears in the bullet list, the Run section, and Contract item 2; 'VO first (locks the timeline)' appears in Run and PIPELINE both. This matches the score-3 anchor (mostly efficient but could be tightened); not 4 because the repetition is structural, not just minor trimming.

3 / 5

Actionability

Concrete, executable guidance is present: 'Copy the structure of scripts/config.example.json → config.json, fill the creative fields from the recipe choices', an explicit ordered chain ('VO first (locks the timeline) → nano-banana CGI plates → PIL screen composites → ... → 1.15x speed + grain'), and named bundle files. Matches score 4 (mostly executable, concrete references with minor gaps); not 5 because the body contains no commands/code itself and defers the executable steps to PIPELINE.md/README.md, whose working scripts live in an unshipped source-run directory ('clients/masterclass/ad-runs/...').

4 / 5

Workflow Clarity

A clear sequence is given twice (Run section and the bullet pipeline) with a per-beat decision gate as a checkpoint: 'If a Kling beat garbles the burst-out UI, distorts the phone, or animates the screen, fall that beat to a FREE Ken-Burns push-in — never ship a garbled beat'. Matches score 4 (clear sequence, most checkpoints present); not 5 because there are no explicit validation steps on the FREE outputs (e.g. checking composite alignment, screen-bbox detection, or measured VO durations) — the only verification is the Kling-garble judgment.

4 / 5

Progressive Disclosure

The body is a clean overview and appropriately splits detail into one-level-deep, clearly signaled references: 'See scripts/README.md for the full FREE-assembly detail and scripts/PIPELINE.md for the config-field → source-step map' — and all three referenced files (scripts/README.md, scripts/PIPELINE.md, scripts/config.example.json) exist in the bundle with content matching their signaled roles. Matches the score-5 anchor (clear overview, well-signaled one-level-deep references, easy navigation).

5 / 5

Total

16

/

20

Passed

Description

72%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 unusually specific and comprehensive about what the skill does, with an explicit 'Use for...' clause. Its weaknesses are trigger-term naturalness (users would say 'app promo/sizzle video', not 'cgi-app-sizzle' or 'nano-banana') and a 'when' clause that names only an internal format identifier.

Suggestions

Add user-side synonyms to the trigger clause, e.g. 'Use when the user asks for a 3D-CGI app sizzle, app promo video, product film, or app store trailer' instead of only the internal format name 'cgi-app-sizzle'.

Replace or gloss internal jargon in the opening ('nano-banana CGI plates', 'Kling 3.0 i2v') with at least one natural phrase (e.g. 'AI-generated CGI plates' / 'image-to-video clips') so the description matches what users actually say.

State the boundary that distinguishes this from sibling video-format skills (e.g. 'not UGC, not physical-product shoot' is already in the body — surface it in the description) to reduce overlap risk.

DimensionReasoningScore

Specificity

Quotes multiple concrete actions with comprehensive coverage: 'nano-banana CGI plates', 'PIL compositing of the REAL App Store screenshots onto the bezel + burst-out overlays', 'Kling 3.0 i2v steady-float per beat with a per-beat Ken-Burns FFmpeg push-in fallback', 'VO/music mix (sidechain duck, loudnorm) + 1.15x speed + anti-AI grain finalize'. This matches the score-5 anchor (multiple specific concrete actions, comprehensive); score 4 would require minor coverage gaps, but every pipeline stage is named.

5 / 5

Completeness

The 'what' is explicit and detailed (full assembly pipeline enumerated), and a 'when' clause is present ('Use for the cgi-app-sizzle video format'), so both exist — matching the score-4 anchor. Not 5 because the 'when' is a single reference to an internal format name with no concrete trigger phrases or user-side synonyms; not 3 because the 'when' is explicit, not merely implied.

4 / 5

Trigger Term Quality

Some relevant keywords exist ('3D-CGI app sizzle', 'App Store screenshots', 'video format') but the natural-phrases users would say are thin — the only trigger is the internal format name 'Use for the cgi-app-sizzle video format', and terms like 'nano-banana', 'Kling 3.0 i2v', and 'recipe choices' are internal jargon. Matches the score-3 anchor (relevant keywords but missing common variations or synonyms such as 'promo video', 'app demo', 'product film'); not 4 because a user asking generically for an app promo video would not naturally say these terms.

3 / 5

Distinctiveness Conflict Risk

The niche is clear ('3D-CGI app sizzle' with a very specific plates/compositing/i2v pipeline), so it is mostly distinct with minimal conflict risk — matching score 4. Not 5 because it shares trigger surface with sibling video-format skills in the same recipe family (the 'recipe orchestrates the spend' framing implies a family of closely related capabilities), leaving minor overlap risk.

4 / 5

Total

16

/

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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