AD tencent-cloud-cos
腾讯云对象存储(COS)和数据万象(CI)集成技能。覆盖文件存储管理、AI处理和知识库三大核心场景。 存储场景：上传文件到云端、下载云端文件、批量管理存储桶文件、获取文件签名链接分享、查看文件元信息。 图片处理场景：图片质量评估打分、AI超分辨率放大、AI智能裁剪、二维码/条形码识别、添加文字水印、获取图片EXIF信息、 缩放、裁剪、旋转、格式转换。 文档处理场景：Word/Excel/PPT等办公文档转PDF、文档预览。 媒体处理场景：视频智能封面提取、视频转码、视频截帧、获取媒体信息。 内容审核场景：图片/视频/音频/文本/文档内容审核，检测违规内容。 智能语音场景：语音识别（音频转文字）、语音合成（文字转语音）、音频降噪、人声分离。 文件处理场景：文件哈希计算、文件压缩打包、文件解压。 内容识别场景：图片标签识别、OCR文字识别。 知识库场景：一键创建知识库、上传文档到知识库、从知识库检索内容片段。 智能检索场景：MetaInsight以图搜图、以文搜图、人脸搜索、元数据检索、多模态文档检索。 当用户提到以下关键词或口语化表述时应触发此技能： 上传到COS、腾讯云存储、对象存储、云存储、存储桶、Bucket、 图片处理、图片压缩、图片放大、超分辨率、抠图、裁剪、二维码识别、水印、 文档转换、转PDF、视频封面、智能封面、以图搜图、图片搜索、MetaInsight、 COS上传、COS下载、签名URL、腾讯云文件、数据万象、CI处理、 内容审核、图片审核、视频审核、文本审核、语音识别、语音合成、降噪、人声分离、 OCR、文字识别、图片标签、 创建知识库、建一个知识库、上传到知识库、往知识库里加文件、查询知识库、 从知识库找、搜索知识库、知识库检索、文档检索、文档搜索。 即使用户没有明确提到COS或腾讯云，只要涉及"把文件传到云上"、"生成下载链接"、 "处理云端图片"、"帮我建个知识库"、"把文档放进知识库"、"从知识库里搜一下"、 "加密COS凭证"、"COS密钥不安全"、"加密一下COS密钥"、"保护COS密钥"等意图，也应该触发此技能。
腾讯云对象存储(COS)和数据万象(CI)集成技能。覆盖文件存储管理、AI处理和知识库三大核心场景。 存储场景：上传文件到云端、下载云端文件、批量管理存储桶文件、获取文件签名链接分享、查看文件元信息。…
As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
The same skill appears in 1 more place: ClawHub
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: 6. 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") - note
frontmatter-keyunknown frontmatter key "description_zh" - note
frontmatter-keyunknown frontmatter key "description_en"
Process rating: all ten parameters 39/100
- 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. 12 mutating operations with no state check
- 40Consistency. Frontmatter name (tencent-cloud-cos) differs from the folder (testtesttesttest)
- 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
- 100Steps. 54 steps
- 100Execution cost. Instruction body is 3613 tokens
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)
- +3Description length 888: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -220 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 10 example trigger phrases
- +4Structure: 33 headings
- +3Step-by-step instructions: 54 items
- +4Has examples (22 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: 77.