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AF osint-mcp

Run OSINT investigations from chat — email, username, domain, IP, phone, photo geolocation, plus news, social, and link-graph intelligence — using the osint-mcp tools.

ClawHub Agent Skills author: Samir v2.4.3 MIT-0 2 files body ≈ 656 tokens Open the sourceclawhub.ai↗ analyzed 26 h ago

Run OSINT investigations from chat — email, username, domain, IP, phone, photo geolocation, plus news, social, and link-graph intelligence — using the…

As a process F 41/100 · Will not run — References files that are not bundled: examples/openclaw.json

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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
F
41/100
Will not run
References files that are not bundled: examples/openclaw.json
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: examples/openclaw.json
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 41/100

Will not run. References files that are not bundled: examples/openclaw.json
  • 0Tools and files. 1 referenced file(s) missing: examples/openclaw.json
  • 0Result and completion. Does not say what the result is
  • 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
  • 55Failures and branches. 1 branches
  • 100Steps. 17 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 656 tokens
  • 100Running it twice. No mutating operations

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 167: enough signal without eating the budget
  • +4Structure: 4 headings
  • +3Step-by-step instructions: 17 items
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: clean
The available evidence does not show malicious behavior, but the skill’s broad trigger wording could make it run for loosely related investigation requests.
LLM: benign (medium) · VirusTotal: · 10 Jun 2026