AD gemini-mcp
Generate and edit images, video, and music with Google Gemini models via MCP. Use when the user asks to generate, create, or edit images (Gemini / Nano Banana), produce a consistent set of images, compose/blend multiple images, generate a short video (text→video or image→video, via the omni model), or generate music/audio clips (via Lyria). Triggers on phrases like "generate an image of", "edit this image with Gemini", "create a set of consistent images", "make a video of", "generate a video", "generate music", "make a song/audio clip", "use Nano Banana to make", or any request to produce images, video, or music via the Gemini API. Requires the @chrischall/gemini-mcp package installed and the gemini server registered (see Setup below).
Generate and edit images, video, and music with Google Gemini models via MCP.
As a process D 48/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 1
✓ No critical or high findings
Medium and low: 1
-
low Exfiltration
net-credential-useSKILL.md:187Credential used in a network call (verify the destination is the intended service) (destination host is a configured variable)$ curl -X POST https://<hosted deployment>/upload -H "Authorization: Bearer $TOKEN" \
variable host
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 5437 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 48/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 12 mutating operations with no state check
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Execution cost. Instruction body is 5437 tokens
- 100Steps. 48 steps
- 100Consistency. Name and required fields are in place
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 8 example trigger phrases
- +3Description length 745: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 48 items
- +4Has examples (15 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.