CC phone-messages
Read and answer messages in the chat apps on the user's phone (微信 and the like) through the screen: catch up, draft a reply in the user's voice, send only text they confirmed. Use when the user asks what someone said on WeChat or wants a chat answered.
The skill reads messages in WeChat and similar apps directly from the phone screen, captures text, drafts a reply in the user's voice, and sends only what they approve. Promises to handle chats without manual copying.
The code contains 537 tokens with no critical errors. Safety score is 100, quality is 69. But the skill has never run on models and wasn't tested in a sandbox. The description doesn't explain how it captures screen text—no mention of OCR, screenshot parsing, or API access to these apps. Support lists eight platforms, but without tests that reads like wishful thinking.
Don't install. The skill has an 'ok' status, but whether it actually works is unknown. Test it on your model first.
Read and answer messages in the chat apps on the user's phone (微信 and the like) through the screen: catch up, draft a reply in the user's voice, send only…
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: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Read and answer messages in the chat apps on the user's phone (微信 … ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - note
frontmatter-keyunknown frontmatter key "channel"
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
- 30Running it twice. 6 mutating operations with no state check
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 11 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 537 tokens
- 100Progress reporting. Reports progress
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 252: enough signal without eating the budget
- +4Structure: 5 headings
- +3Step-by-step instructions: 11 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.