AD ducc-helper
京东 DUCC 配置中心(泰山 taishan.jd.com/ducc、后端 console.ducc.jd.com)统一入口，让 agent 能读写发布 DUCC 配置。零配置认证（本机京ME客户端换 sso.jd.com，无需浏览器/手填token）。当用户想要「查 DUCC 命名空间/应用配置空间」「列某命名空间下的配置文件」「看配置文件有哪些环境/profile(如 dev/common/生产配置/预发配置)」「读某个配置项的值/key value」「查 DUCC 某开关/参数当前配的啥」「改 DUCC 配置项/新增配置项/删除配置项」「发布 DUCC 配置/全量发布/灰度发布/分批发布」「按 10%->30%->60%->100% 灰度」「等前批IP成功再发下一批」，或提到 DUCC、ducc、泰山配置、taishan、命名空间、nsId、配置文件、profile、配置项、consoleducc、灰度发布、编排模板、orchestrate 时，都应使用本技能——即使用户没明确说技能名。命名空间/配置文件/profile 都可传中文 code(如 pop_customs_center / center_config / common)自动解析为内部ID。改/增/删只影响草稿(直接执行)，发布(真正生效到线上)默认只预演，加 --confirm 才下发。
京东 DUCC 配置中心(泰山 taishan.jd.com/ducc、后端 console.ducc.jd.com)统一入口，让 agent 能读写发布 DUCC 配置。零配置认证（本机京ME客户端换 sso.jd.com，无需浏览器/手填token）。当用户想要「查 DUCC…
As a process D 46/100 · 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.
- 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: 10. 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 46/100
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 22 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1285 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
- +1No license
- +2Single-language instructions
- +3Description length 589: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.