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BA setup-local-testnet

Spin up a local Anvil testnet with Uniswap deployed and pre-seeded liquidity. One command gives you a full development environment with funded accounts, real Uniswap pools, and zero gas costs. Use when developing, testing, or demoing Uniswap agent workflows.

Not recommendedcritical or high security findings
modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 1 975 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Spin up a local Anvil testnet with Uniswap deployed and pre-seeded liquidity.

As a process A 80/100 · Runs to the end — weak spots: result and completion, running it twice

ProcedureAI 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
78/100
safety, quality, tests
Safety 60%
72
Quality 40%
86
Run on models
none yet
Process rating
A
80/100
Runs to the end
Result and completion w 14
0
Running it twice w 4
30
Inputs and preconditions w 11
70
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
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 · 7

  • high Dangerous commands cmd-pipe-to-shell SKILL.md:65
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    Install: curl -L https://foundry.paradigm.xyz | bash && foundryup
Medium and low: 6
  • medium Dangerous commands cmd-pipe-to-shell SKILL.md:149
    Downloads and executes remote code from an unrecognised host (pipe to shell) (documentation table row)
    | `TESTNET_ANVIL_NOT_FOUND`      | "Anvil (Foundry) is not installed."                                      | Install: `curl -L https://foundry.paradigm.xyz \| bash && foundryup` |
    table
  • low Secrets in code secret-high-entropy-token SKILL.md:99
    High-entropy token-like string (may be an id, hash or a credential)
    │ 1  0xf3…266 10,000    1,000,000  │
  • low Secrets in code secret-high-entropy-token SKILL.md:100
    High-entropy token-like string (may be an id, hash or a credential)
    │ 2  0x70…9C8 10,000    1,000,000  │
  • low Secrets in code secret-high-entropy-token SKILL.md:101
    High-entropy token-like string (may be an id, hash or a credential)
    │ 3  0x3C…3BC 10,000    1,000,000  │
  • low Secrets in code secret-high-entropy-token SKILL.md:105
    High-entropy token-like string (may be an id, hash or a credential)
    V3Factory:                      0x1F…984
  • low Secrets in code secret-high-entropy-token SKILL.md:106
    High-entropy token-like string (may be an id, hash or a credential)
    NonfungiblePositionManager:     0xC3…E88

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

✓ No remarks against the Agent Skills spec

Process rating: all ten parameters 80/100

  • 0Result and completion. Does not say what the result is
  • 30Running it twice. 3 mutating operations with no state check
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 26 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 7 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1975 tokens
  • 100Progress reporting. Reports progress

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
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 258: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 26 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.