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gemini-omni-flash-api

Use this skill for generative video editing, text-to-video, image-referenced video generation, first-frame-to-video, first-and-last-frame transitions, and video extensions using Gemini Omni 1.1 Flash (gemini-omni-1.1-flash) via the official google-genai SDK. Includes workflows for pre-processing/optimizing high-resolution or long source videos with ffmpeg, stripping audio for full sound regeneration, and handling turn-by-turn video editing and parallel execution.

Quality

78%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/.agents/skills/gemini-omni-flash-api/SKILL.md

The canonical home for this skill is gemini-omni-flash-api in boranfurkan/reproducer-hackathon

SKILL.md
Quality
Evals
Security

Quality

Content

65%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.

An exceptionally actionable body — every workflow has executable commands, real flags, and a complete batch example — and script navigation is accurate against the actual bundle. It is held back by redundancy (extension rules repeated in four places, 11 near-identical tag bullets), missing validation checkpoints for batch operations, and the absence of any progressive-disclosure layer, leaving everything in one long SKILL.md.

Suggestions

Consolidate the extension guidance scattered across 'Core capabilities', the generate_video.py extension examples, 'Prompts for extending a video', and 'Video extension constraints and guidelines' into a single section to remove repetition and cut tokens.

Add an explicit validation checkpoint to the Workflow section (e.g. verify each batch job's output exists and open failed jobs' error logs before reporting to the user), which would also lift the batch path above the workflow-clarity cap.

Move the detailed prompting guide (tag declarations, timing, meta prompting, text-in-video) into a references/prompting.md file and keep a short summary with a one-level-deep pointer in SKILL.md, reducing the main file to an overview.

DimensionReasoningScore

Conciseness

The body is dense and free of generic-concept padding, but has real tightening opportunities: extension rules are repeated across four sections ("Core capabilities", "Video extension (extend an existing video)", "Prompts for extending a video", "Video extension constraints and guidelines"), the "Declaring sources and references" section lists 11 near-identical tag bullets, and time-sensitive version pins ("google-genai >= 2.19.0", "Python >= 3.10") sit outside any deprecated section. This matches 'mostly efficient but could be tightened' rather than the 'minor instances' of the level 4 anchor.

3 / 5

Actionability

Every capability ships a copy-paste-ready command with concrete flags and defaults — e.g. './scripts/video/generate_video.py "A close-up of a cat drinking tea" --output media/cat_tea.mp4', '--resolution 1080p --timeout 900', 'pip install -U google-genai', plus a fully executable 5-job batch JSON example. Coverage of common cases is complete.

5 / 5

Workflow Clarity

The Workflow section gives a clear 3-step sequence (analyze request, run SDK scripts, retrieve output) and documents failure signatures ("total_output_tokens: 0"), but verification is implicit — inspect_video.py is presented as a tool rather than wired in as a validation checkpoint, and the parallel batch paths (--batch, --prompts-file --concurrency 3) have no described per-job result verification. Per the rubric's cap, batch operations without feedback loops cap workflow clarity at 3.

3 / 5

Progressive Disclosure

The bundle is clean — all four referenced scripts (upload_file.py, generate_video.py, inspect_video.py, prep_video.py) exist exactly one level deep — but there is no reference layer at all: the ~150-line prompting guide (tag syntax, timing, meta prompting) and full dependency details are inlined in a ~450-line SKILL.md instead of being split into a separate reference file. This matches 'content that should be separate is inline' at level 3 rather than the well-split structure of level 4.

3 / 5

Total

14

/

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, highly specific description that clearly names the model, SDK, and all major task types with an explicit trigger clause. Its only weakness is that the 'when' guidance mirrors the capability list rather than adding distinct user-side trigger phrasings or common synonyms.

DimensionReasoningScore

Specificity

The description enumerates six concrete capabilities ("generative video editing, text-to-video, image-referenced video generation, first-frame-to-video, first-and-last-frame transitions, and video extensions") plus three auxiliary workflows ("pre-processing/optimizing high-resolution or long source videos with ffmpeg, stripping audio for full sound regeneration"), matching the comprehensive-coverage anchor. It exceeds the 'minor gaps' level 4 anchor because it covers the model's full capability surface with concrete action verbs.

5 / 5

Completeness

Both what and when are present — the explicit trigger clause "Use this skill for generative video editing, text-to-video..." satisfies the 'Use when...' requirement, so it is not capped at 3. The when is explicit but is a restatement of the capability list rather than distinct user-side trigger conditions (e.g. "when the user asks to generate or edit a video"), matching the level 4 anchor where 'when' could be more specific.

4 / 5

Trigger Term Quality

Good natural keyword coverage: "video editing", "text-to-video", "video extensions", "image-referenced video generation" are phrases users would naturally say. Falls short of the 5 anchor because common variations like "make/create a video", "animate an image", or file extensions (.mp4) are absent.

4 / 5

Distinctiveness Conflict Risk

The repeated model qualifier "using Gemini Omni 1.1 Flash (gemini-omni-1.1-flash) via the official google-genai SDK" establishes a clear niche with minimal conflict risk, distinguishing it even from sibling Gemini video-model skills. It fits the 'clear niche with distinct triggers' anchor better than the 'minor overlap risk' level 4 anchor.

5 / 5

Total

18

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 3 deeper-than-1-level

Warning

referenced_paths_exist

Referenced path issues: 6 deeper-than-1-level

Warning

Total

14

/

16

Passed

Repository

boranfurkan/planb-hackathon

Path

skills/.agents/skills/gemini-omni-flash-api/SKILL.md

Reviewed

Table of Contents

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