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BF Intelligence Ingestion

Auto-analyze URLs/info for OpenClaw strategic value, classify, create Obsidian notes, update memory. Use when user shares a URL, article, tweet, or any external info source.

ClawHub Agent Skills author: 2233admin v1.0.0 6 files body ≈ 1 298 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process F 52/100 · Will not run — References files that are not bundled: URL

AnalyzerObsidianWriting and documentsInfrastructuretype 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
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
F
52/100
Will not run
References files that are not bundled: URL
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning missing-ref reference to a missing file: URL

Process rating: all ten parameters 52/100

Will not run. References files that are not bundled: URL
  • 0Tools and files. 1 referenced file(s) missing: URL
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 40Consistency. Frontmatter name (Intelligence Ingestion) differs from the folder (openclaw-skill-intelligence-ingestion)
  • 100Steps. 26 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 3 branches, has a failure section
  • 100Execution cost. Instruction body is 1298 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress

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 173: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 26 items
  • +4Has examples (5 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: suspicious
The skill is not deceptive, but it automatically fetches shared content and saves it into local notes and memory without a clear consent step.
LLM: suspicious (high) · VirusTotal: suspicious · 28 May 2026