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Ranks your daily AI news feed by personal relevance — scores every article and surfaces the most useful ones first. To fetch X/Twitter posts, the daily run reads your local Chrome x.com cookies (via browser-cookie3, in-memory only) and calls the twitter-cli subprocess; it may auto-detect a local proxy on 127.0.0.1 to reach x.com, and writes reports/history/dedup state to your local data_dir. Sources include HuggingFace Papers, OpenAI, Anthropic, DeepMind, Simon Willison, GitHub Trending, HN, Reddit, and more, plus X/Twitter accounts.

ClawHub Agent Skills author: Pudge v1.0.5 MIT-0 16 files body ≈ 2 683 tokens Open the sourceclawhub.ai↗ analyzed 18 h ago

Ranks your daily AI news feed by personal relevance — scores every article and surfaces the most useful ones first.

As a process C 55/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

GeneratorGitHubAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
C
55/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 0. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "emoji"
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 55/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, read, web, python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 85Steps. 36 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2683 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)
  • +2Single-language instructions
  • +3Description length 539: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 36 items
  • +3Output format is stated explicitly
  • +4Has examples (7 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
The skill is a coherent AI news digest tool, but its default daily run reads local Chrome X/Twitter session cookies and passes them to a subprocess without a clear per-run opt-in.
LLM: suspicious (high) · 25 Jun 2026