CF douyin-comment-collector
抖音数据采集技能(评论采集 + 账号主页作品抓取)。① 评论:手上有抖音视频完整 URL、短链 v.douyin.com 转发链接或数字 aweme_id,想把评论抓下来做舆情/选题/复盘/词频统计时使用;② 主页作品:给定账号主页 URL / 短链 / sec_uid,抓取该账号发布的作品标题(desc)与发布时间(create_time),支持 --since/--until 本地时间区间过滤,正是「拉取指定账号在指定时间发布内容的标题和时间」场景。评论提供两条路径:无头浏览器游客态(免登录)与纯 Python 签名(a_bogus)+mssdk 真 msToken 创作者接口(需本人 cookie);主页作品用浏览器拦截 aweme/post 接口,支持 --since/--until 时间过滤与 --analyze 按天分布统计。统一入口 douyin.py 一键路由评论/作品两个子命令。支持可选 jieba 词频分析;全自包含、可独立安装。不适用于快手/小红书/视频号等其他平台(那是别的技能),也不绕过登录做越权抓取——仅采集你有权访问的公开数据。
抖音数据采集技能(评论采集 + 账号主页作品抓取)。① 评论:手上有抖音视频完整 URL、短链 v.douyin.com 转发链接或数字 awemeid,想把评论抓下来做舆情/选题/复盘/词频统计时使用;② 主页作品:给定账号主页 URL / 短链 /…
As a process F 33/100 · No process to follow — References files that are not bundled: scripts/douyin_cookie.json
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Secrets in code
secret-high-entropy-tokenscripts/mstoken.py:36High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)_CUSTOM_B64 = "Dkdp…B80/Mfvw…R25+WUAl…tCe"
quoted -
low Secrets in code
secret-high-entropy-tokenscripts/sign/ab_pure.py:30High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)ALPHABET_S3 = "ckdp…B80/Mfvw…R25+WQAl…tCe"
quoted
Files scanned: 19. 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
missing-refreference to a missing file: scripts/douyin_cookie.json - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 33/100
- 0Tools and files. 1 referenced file(s) missing: scripts/douyin_cookie.json
- 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. 2 mutating operations with no state check
- 100Steps. 32 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2268 tokens
- low The response is described with custom markup (7 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
- +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 486: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 32 items
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 9 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.