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BD geopolitical-analyst

Live geopolitical intelligence analysis with 39 analytical modules and real-time data integration. No API keys required.

ClawHub Agent Skills author: Nima Ansari v0.1.2 MIT-0 52 files body ≈ 617 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerInfrastructuretype 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
79/100
safety, quality, tests
Safety 60%
89
Quality 40%
65
Run on models
none yet
Process rating
D
41/100
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

  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 · 11

✓ No critical or high findings

Medium and low: 11
  • low Risky intent intent-offensive-security references/ach.md:132
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    ## Integration with Red Team Check (Step 8 of main workflow)
  • low Risky intent intent-offensive-security references/ach.md:134
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    ACH and the Red Team Check are complementary, not redundant:
  • low Risky intent intent-offensive-security references/ach.md:136
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - **Red Team** challenges the conclusion (what would have to be true for us to be wrong?)
  • low Risky intent intent-offensive-security references/ach.md:138
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    Run ACH first. Then Red Team the ACH output.
  • low Risky intent intent-offensive-security references/art-of-war.md:302
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    **Triggered:** In Step 5 (Actor Assessment) and Step 8 (Red Team)
  • low Risky intent intent-offensive-security references/credible-commitment.md:212
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    **Triggered:** In Step 5 (Actor Mapping) and Step 8 (Red Team)
  • low Risky intent intent-offensive-security references/cyber-operations.md:37
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - Ransomware, DDoS, data theft
  • low Risky intent intent-offensive-security references/information-asymmetry.md:233
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    **Triggered:** In Step 5 (Actor Assessment) and Step 8 (Red Team)
  • low Risky intent intent-offensive-security references/scenario-modeling.md:231
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - Red team analysis (Step 8)
  • low Risky intent intent-offensive-security references/threshold-analysis.md:232
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    **Triggered:** In Step 5 (Actor Assessment) and Step 8 (Red Team)
  • low Risky intent intent-offensive-security SKILL.md:24
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
    - **9-step intelligence workflow** — data → bias → actors → economics → networks → patterns → info warfare → red team → scenarios
    detector

Files scanned: 52. 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 "repository"

Process rating: all ten parameters 41/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (geopolitical-analyst) differs from the folder (geopolitical-analyst-skill)
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 13 steps
  • 100Execution cost. Instruction body is 617 tokens
  • 100Running it twice. No mutating operations
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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
  • -447 reference files, but SKILL.md never points to them: the model will not open them
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 120: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 13 items
  • +4Has examples (4 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

External checks

ClawHub: suspicious
The skill appears aimed at geopolitical analysis, but its main documentation materially understates external data sharing, optional credentials, missing advertised runtime files, and local tracking behavior.
LLM: suspicious (high) · VirusTotal: · 29 May 2026