AF datanexus-sdk
DataNexus 数据采集 SDK 接入助手，覆盖 SDK 选型、接入开发、事件埋点、联调对账、质量评估、问题排查六大能力，以及面向 AI IDE 的自动化接入（Beta）和已接入项目接入体检能力。Use when user mentions "小程序SDK", "小游戏SDK", "APP SDK", "iOS SDK", "Android SDK", "鸿蒙SDK", "JS SDK", "SDK初始化", "事件上报", "埋点", "行为清单", "action_type", "START_APP", "PURCHASE", "REGISTER", "user_action_set_id", "secret_key", "数据源ID", "SDK接入流程", "SDK质量看板", "数据对账", "联调", "SDK报错", "code 51000", "data not valid", "SDK合规", "必报事件", "事件覆盖率", "接入体检", "接入审计", or asks to "接入SDK", "自动接入", "帮我接入", "生成接入代码", "选择SDK类型", "排查SDK上报问题", "检查埋点质量", "检查接入", "审计接入", "audit", "体检".
DataNexus 数据采集 SDK 接入助手，覆盖 SDK 选型、接入开发、事件埋点、联调对账、质量评估、问题排查六大能力，以及面向 AI IDE 的自动化接入（Beta）和已接入项目接入体检能力。Use when user mentions "小程序SDK", "小游戏SDK", "APP SDK", "iOS…
As a process F 28/100 · Will not run — References files that are not bundled: references/通用/排障/客户端自判沉默注册的反面案例.md
How to improve
- The text references files that are not there: add them or drop the references.
- 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: 47. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/通用/排障/客户端自判沉默注册的反面案例.md
Process rating: all ten parameters 28/100
- 0Tools and files. 1 referenced file(s) missing: references/通用/排障/客户端自判沉默注册的反面案例.md
- 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. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (datanexus-sdk) differs from the folder (datanexus-sdk-skills)
- 100Steps. 69 steps
- 100Execution cost. Instruction body is 2184 tokens
- low 10 top-level sections: this looks like several domains in one skill
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
- -245 emoji in the instructions: noise for the model
- -33 of 8 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +5Description quotes 22 example trigger phrases
- +3Description length 557: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 69 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.