BD link-skills
Link 产品全链路开发技能，覆盖需求分析、方案设计（技术方案/数据库设计/接口设计）、 编码开发（基于 link 标准）、测试部署上线、后续运维的完整生命周期。 适用于工作目录 D:\develop\code\cdfai 下的 link CRM+AI 微服务系统。 当用户需要为 link 项目开发新功能、设计接口、修改代码、排查问题、部署上线或进行运维操作时触发此技能。 关键词：link开发、link接口、link部署、link运维、CRM开发、AI助手开发、知识库开发、企微同步、微服务开发。
Link 产品全链路开发技能，覆盖需求分析、方案设计（技术方案/数据库设计/接口设计）、 编码开发（基于 link 标准）、测试部署上线、后续运维的完整生命周期。 适用于工作目录 D:\develop\code\cdfai 下的 link CRM+AI 微服务系统。 当用户需要为 link…
As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Exfiltration
net-credential-usereferences/troubleshooting.md:98Credential used in a network call (verify the destination is the intended service)curl -H "Authorization: Bearer $TOKEN" ...
Files scanned: 15. 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 45/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 4 mutating operations with no state check
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 98 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2182 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
- +1No license
- +2Single-language instructions
- +3Description length 250: enough signal without eating the budget
- +4Structure: 30 headings
- +3Step-by-step instructions: 98 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (7 of 7)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.