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AF community-intel

Automated community intelligence gathering for any open-source project or product. Searches Reddit, Hacker News, Twitter/X, GitHub, and YouTube for mentions, use cases, tips, complaints, and trends. Compiles findings into structured reports. Use when you want to monitor community sentiment, track adoption, discover use cases, or stay on top of ecosystem developments around a project.

ClawHub Agent Skills author: npfaerber v1.1.0 2 files body ≈ 1 593 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process F 45/100 · Will not run — References files that are not bundled: url

ReferenceGitHubYouTubeDiscordInfrastructureData and analyticsCustomer supporttype 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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
F
45/100
Will not run
References files that are not bundled: url
Tools and files w 18
0
Result and completion w 14
0
Failures and branches w 10
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: url

Process rating: all ten parameters 45/100

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
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 23 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1593 tokens
  • 100Running it twice. No mutating operations
  • 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 386: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (5 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: clean
This skill is a disclosed, instruction-only community monitoring workflow with expected scheduled research, local logging, and optional report delivery.
LLM: benign (high) · VirusTotal: benign · 28 May 2026