BC freepik
Generate images, videos, icons, audio, and more using Freepik's AI API. Supports Mystic, Flux, Kling, Hailuo, Seedream, RunWay, Magnific upscaling, stock content, and 50+ models. Use when user wants to generate or edit images, create videos, generate icons, produce audio, or search stock content.
Generate images, videos, icons, audio, and more using Freepik's AI API.
As a process C 56/100 · Has gaps — weak spots: result and completion, inputs and preconditions, execution cost
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
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
-
medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bash(curl, Bash(curlallowed-tools: Bash(curl *api.freepik.com*) Bash(curl **.freepik.com*) Bash(jq *) Bash(mkdir -p ~/.freepik/*)
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 8541 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 56/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 10 mutating operations with no state check
- 40Execution cost. Instruction body is 8541 tokens: crowds the task out of the window
- 50When it triggers. No condition that starts the skill
- 55Failures and branches. 1 branches
- 85Steps. 146 steps, 1 vague phrases
- 100Tools and files. Tools declared in frontmatter
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- low The response is described with custom markup (16 tags): a typed call is more reliable
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
- +5Description has no quoted example phrases that should trigger the skill
- +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
- +3Description length 297: enough signal without eating the budget
- +4Structure: 55 headings
- +3Step-by-step instructions: 146 items
- +4Has examples (47 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.