SKILLEMALL.ai
GitHub ↗ RU Sign in

BC web3-investor

AI-native DeFi investment intelligence. Discover, analyze, and compare yield opportunities across 2,500+ protocols with intent-aware search, LLM-powered deep analysis, 7-dimension risk scoring, DeFi security scanning, smart money sentiment, and multi-round conversational refinement. All intelligence runs server-side — zero API keys on the client.

ClawHub Agent Skills author: bevanding v3.8.2 MIT-0 11 files · 1 script body ≈ 3 633 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 57/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

IntegrationAI and agentsInfrastructuretype 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%
64
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
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 · 11

✓ No critical or high findings

Medium and low: 11
  • low Secrets in code secret-high-entropy-token config/protocols.json:8
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "primary_contract": "0x87…4E2",
    quoted
  • low Secrets in code secret-high-entropy-token config/protocols.json:26
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "primary_contract": "0x87…4E2",
    quoted
  • low Secrets in code secret-high-entropy-token config/protocols.json:34
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "primary_contract": "0xc3…dc3",
    quoted
  • low Secrets in code secret-high-entropy-token config/protocols.json:52
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "primary_contract": "0xc3…dc3",
    quoted
  • low Secrets in code secret-high-entropy-token config/protocols.json:60
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "primary_contract": "0xae…E84",
    quoted
  • low Secrets in code secret-high-entropy-token references/protocols.md:8
    High-entropy token-like string (may be an id, hash or a credential)
    - **Contract**: 0x87…4E2
  • low Secrets in code secret-high-entropy-token references/protocols.md:16
    High-entropy token-like string (may be an id, hash or a credential)
    - **Contract**: 0xc3…dc3
  • low Secrets in code secret-high-entropy-token references/protocols.md:34
    High-entropy token-like string (may be an id, hash or a credential)
    - **Contract**: 0xae…E84
  • low Secrets in code secret-high-entropy-token references/protocols.md:42
    High-entropy token-like string (may be an id, hash or a credential)
    - **Contract**: 0xae…393
  • low Secrets in code secret-high-entropy-token references/protocols.md:52
    High-entropy token-like string (may be an id, hash or a credential)
    - **Factory**: 0x1F…984
  • low Secrets in code secret-high-entropy-token SKILL.md:424
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - **Address**: `0x1F…a3e`
    quoted

Files scanned: 11. 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 "homepage"

Process rating: all ten parameters 57/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 29 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3633 tokens
  • low 10 top-level sections: this looks like several domains in one skill

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
  • -43 reference files, but SKILL.md never points to them: the model will not open them
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 348: enough signal without eating the budget
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (13 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: clean
This is a disclosed remote DeFi research skill, but users should avoid sending private financial details or secrets to the Antalpha MCP server.
LLM: benign (medium) · VirusTotal: · 29 May 2026