SKILLEMALL.ai

BD gigaverse

Enter the Gigaverse as an AI agent. Create a wallet, quest through dungeons, battle echoes, and earn rewards. The dungeon awaits.

modbender/skill-library-mcp Agent Skills author: modbender MIT 23 files · 4 scripts body ≈ 3 939 tokens Open the sourcegithub.com analyzed 2 d ago

Enter the Gigaverse as an AI agent.

As a process D 35/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
78/100
safety, quality, tests
Safety 60%
84
Quality 40%
69
Run on models
none yet
Process rating
D
35/100
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

Risky intent medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The purpose itself is risky: wallets, browser password stores, offensive security. Even an honest implementation gives the agent access to things that cost money.

For the author

Explain in the description why the access is needed and how it is limited; add tests that show refusals on dangerous requests.

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 · 8

✓ No critical or high findings

Medium and low: 8
  • medium Broad scope meta-agent-memory-dump HEARTBEAT.md
    Agent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokens
    HEARTBEAT.md
  • medium Risky intent intent-wallet-secrets SKILL.md:438
    Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target
    | `~/.secrets/gigaverse-private-key.txt` | Your wallet private key |
  • low Secrets in code secret-high-entropy-token references/onboarding.md:107
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    Call the **AccountSystem** contract at `0x5f…C00`.
    quoted
  • low Secrets in code secret-high-entropy-token references/onboarding.md:119
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    address: '0x5f…C00',
    quoted
  • low Secrets in code secret-high-entropy-token scripts/mint-direct.cjs:16
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    const ACCOUNT_SYSTEM = '0x5f…C00';
    quoted
  • low Secrets in code secret-high-entropy-token scripts/package-lock.json:26
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…p81+8Ob3…L40/b0i7…gQw==",
    detector
  • low Secrets in code secret-high-entropy-token scripts/package-lock.json:88
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha512-+lF0B…kdX+94aG…d8c+B3KT…U6A==",
    detector
  • low Secrets in code secret-high-entropy-token scripts/package-lock.json:231
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…CzX+oOPq…N14+GARU…vzg==",
    detector

Files scanned: 23. 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"
  • note frontmatter-key unknown frontmatter key "docs"

Process rating: all ten parameters 35/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 6 mutating operations with no state check
  • 40Consistency. Frontmatter name (gigaverse) differs from the folder (gigaverse-play)
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 60Steps. 46 steps, 4 vague phrases
  • 100Execution cost. Instruction body is 3939 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 16 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
  • -236 emoji in the instructions: noise for the model
  • -32 of 5 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 129: enough signal without eating the budget
  • +4Structure: 47 headings
  • +3Step-by-step instructions: 46 items
  • +4Has examples (25 code blocks)
  • +4Reference files are cited in the instructions (10 of 10)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.