AD evernote-yinxiang
印象笔记（Yinxiang/Evernote）集成技能。用于创建、读取、搜索、删除笔记，以及管理笔记本和标签。当用户提到"印象笔记"、"evernote"、"创建笔记到印象笔记"、"搜索印象笔记"、"查看笔记"、"笔记同步"、"保存到印象笔记"时触发。仅依赖 requests，无需安装 evernote SDK。
As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 43/100
- 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. 5 mutating operations with no state check
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 12 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 330 tokens
- low The response is described with custom markup (3 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
- +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
- +5Description quotes 4 example trigger phrases
- +3Description length 157: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 12 items
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.
External checks
ClawHub: suspicious
This Evernote/Yinxiang skill is mostly purpose-aligned, but it asks for full note-account access while its dependency and API documentation does not match the included code.
LLM: suspicious (high) · VirusTotal: · 29 May 2026