AD multimodal-memory
Remember and retrieve visual content from conversations. Use when: (1) user sends an image, photo, chart, diagram, or screenshot and wants it saved/remembered; (2) user asks to capture or remember a website, URL, or web page UI; (3) user asks what you've seen before, wants to recall a past image, or searches visual memories; (4) user sends an image to find similar past content.
As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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 · 0
✓ No critical or high findings
Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 39/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 4 mutating operations with no state check
- 40Consistency. Frontmatter name (multimodal-memory) differs from the folder (minds-eye)
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 100Steps. 7 steps
- 100Execution cost. Instruction body is 808 tokens
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 380: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 7 items
- +4Has examples (8 code blocks)
- +3All 5 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.