AC mcm-agent
Help users manage cross-device AI memory. When user explicitly asks to save or recall information, sync it to their cloud memory account. Categorizes saved content into personality, preferences, chat history, and long-term memory. User must configure their API key and explicitly consent before any sync happens. Supports Claude Code, Windsurf, Cursor, Codex, OpenClaw, Hermes Agent, Cline and all major AI agents. Free 200 entries. MCM, memory, agent memory, cloud memory, sync, 记忆同步, 跨设备记忆, 云端记忆, AI记忆, 智能记忆, 对话同步, 长期记忆, 跨平台同步, 记忆管家, AI对话记录, 角色记忆, 偏好记忆, 记忆云
As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "triggers"
Process rating: all ten parameters 59/100
- 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
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 4 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 208 tokens
- 100Running it twice. No mutating operations
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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 559: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 4 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.