SKILLEMALL.ai
GitHub ↗ RU Sign in

CD meme-coin-audit

Meme coin and token security audit

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 1 file body ≈ 4 350 tokens Open the sourcegithub.com↗ analyzed 4 d ago

Meme coin and token security audit

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerSecuritytype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
C
85/100
safety, quality, tests
Safety 60%
95
Quality 40%
71
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
When it triggers w 12
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: meme-coin-audit (sickn33/agentic-awesome-skills)

How to improve

    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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token SKILL.md:200
      High-entropy token-like string (may be an id, hash or a credential)
      address constant ROUTER = 0x7a…88D;
    • low Secrets in code secret-high-entropy-token SKILL.md:201
      High-entropy token-like string (may be an id, hash or a credential)
      address constant WETH = 0xC0…Cc2;
    • low Risky intent intent-offensive-security SKILL.md:304
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - **`triage-validation`** — When deciding if a rug-pull finding qualifies as a bug bounty submission. Workflow primitive: many "rug vector" observations are pre-rug warnings, not exploitable bugs in a
    • low Risky intent intent-offensive-security SKILL.md:307
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
      - **`bb-methodology`** — When confirming engagement mode. Workflow primitive: PART 0 separates "pre-investment due diligence" (this skill's primary use) from "Immunefi bug bounty submission" (differen
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:323
      High-entropy token-like string (may be an id, hash or a credential)
      spl-token display <MINT_ADDRESS> --program-id Toke…uEb

    Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning description-short description under 40 chars: too little signal for triggering
    • note frontmatter-key unknown frontmatter key "risk"
    • note frontmatter-key unknown frontmatter key "source"
    • note frontmatter-key unknown frontmatter key "source_repo"
    • note frontmatter-key unknown frontmatter key "source_type"
    • note frontmatter-key unknown frontmatter key "date_added"
    • note frontmatter-key unknown frontmatter key "license_source"
    • note frontmatter-key unknown frontmatter key "sources"

    Process rating: all ten parameters 46/100

    • 0Result and completion. Does not say what the result is
    • 0When it triggers. No condition that starts the skill
    • 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
    • 30Running it twice. 15 mutating operations with no state check
    • 70Execution cost. Instruction body is 4350 tokens
    • 100Tools and files. No external tools needed
    • 100Steps. 44 steps
    • 100Consistency. Name and required fields are in place
    • low 11 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)
    • +3Description length 34: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Structure: 27 headings
    • +3Step-by-step instructions: 44 items
    • +4Has examples (14 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.