SKILLEMALL.ai

BC rerange

Build, preview, monitor, rerange, close, and risk-check non-custodial Rerange liquid orders using @rerange/wagmi.

ClawHub Agent Skills author: RΞRANGE v1.0.2 MIT-0 13 files body ≈ 3 885 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, consistency

GeneratorGitHubInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
98
Quality 40%
68
Run on models
none yet
Process rating
C
56/100
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Secrets in code secret-high-entropy-token index.js:47
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "  node index.js read 8453 hub 0x88…192 hubConfig '[]' https://mainnet.base.org",
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:52
    High-entropy token-like string (may be an id, hash or a credential)
    node {baseDir}/index.js read 8453 hub 0x88…192 hubConfig '[]' https://mainnet.base.org

Files scanned: 13. 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 56/100

  • 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. 18 mutating operations with no state check
  • 40Consistency. Frontmatter name (rerange) differs from the folder (rerange-skill)
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 73 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Execution cost. Instruction body is 3885 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 10 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (5 tags): a typed call is more reliable

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 113: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 73 items
  • +4Has examples (9 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: clean
This is a disclosed crypto automation helper for Rerange orders, with financial risk but no hidden credential collection, install-time execution, or automatic signing found.
LLM: benign (high) · VirusTotal: · 29 May 2026