BD tencent-ses
腾讯云邮件推送(SES)服务技能，用于通过腾讯云 API 发送邮件。当用户提到"发送邮件"、"邮件推送"、"发邮件给"、 "用某个地址给某人发送模板/邮件内容"时触发。支持完整的邮件发送工作流： (0) 检查 API 密钥配置并按安全配置指南引导用户完成子账号创建和密钥获取， (1) 解析用户指令并在信息缺失时引导用户查询已有资源或创建新资源， (2) 查询和验证发信域名，(3) 管理发信地址， (4) 使用模板或自定义内容发送邮件（自定义内容需先确认权限）， (5) 自动查询邮件发送状态。 当域名验证不通过或创建新域名时，自动启动"邮件域名认证向导"，引导用户完成 SPF/DKIM/DMARC/MX 配置， 并通过全球 DNS 传播检测确认生效状态。 当邮件发送出现认证失败时，自动执行"DNS 问题诊断器"，定位 DNS 配置问题并给出修复方案。 也适用于用户询问"邮件发送状态"、"邮件是否送达"、"域名验证"、"DNS 配置"、"SPF/DKIM/DMARC"等场景。 依赖环境变量 TENCENTCLOUD_SECRET_ID、TENCENTCLOUD_SECRET_KEY 和可选的 SES_REGION、SES_ENDPOINT。
As a process D 37/100 · 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.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 7. 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") - warning
body-longSKILL.md body ≈ 6915 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 37/100
- 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. 23 mutating operations with no state check
- 40Consistency. Frontmatter name (tencent-ses) differs from the folder (tencent-ses-skills)
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70Execution cost. Instruction body is 6915 tokens
- 100Steps. 79 steps
- low 11 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (24 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
- -216 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 7 example trigger phrases
- +3Description length 526: enough signal without eating the budget
- +4Structure: 55 headings
- +3Step-by-step instructions: 79 items
- +4Has examples (30 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.