SKILLEMALL.ai

BD x-rss-feishu-daily

X(Twitter)博主监控→飞书群推送→触发智能体写日报的完整自建流水线。RSSHub(走代理)+Miniflux+自写 relay 中转,Docker Compose 一键部署;内置防 X 风控配置(60~120 分钟轮询、30 分钟缓存、温和刷新脚本);含飞书开放平台全流程(自建应用、机器人进群、外部群对外共享与版本发布、用户身份 OAuth);定时维护脚本(每日日报全量重推、温和刷新、token 轮换)与踩坑合集(webhook 内网开关、新订阅不触发 webhook、直写 integrations 表、open_id 跨应用隔离)。Use when the user wants to monitor X/Twitter bloggers and push updates to a Feishu group, build an RSS-to-Feishu daily report pipeline, deploy RSSHub+Miniflux with anti-ban polling, add X bloggers to Feishu push, or troubleshoot Feishu custom app bot/group/external-sharing/OAuth issues.

ClawHub Agent Skills author: Blink Hsu v1.0.8 MIT-0 9 files · 6 scripts body ≈ 1 529 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

X(Twitter)博主监控→飞书群推送→触发智能体写日报的完整自建流水线。RSSHub(走代理)+Miniflux+自写 relay 中转,Docker Compose 一键部署;内置防 X 风控配置(60~120 分钟轮询、30…

As a process D 49/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

IntegrationDockerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 9. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 49/100

    • 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
    • 30Running it twice. 6 mutating operations with no state check
    • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 12 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1529 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

    • +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
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +3Description length 561: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 12 items
    • +4Has examples (3 code blocks)
    • +3All 6 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: suspicious
    The skill is mostly a coherent RSS-to-Feishu automation package, but its relay exposes an unauthenticated port that can let reachable callers post Feishu messages and trigger report actions through the user's app.
    LLM: suspicious (high) · 3 Oct 2026