SKILLEMALL.ai

CD lp-monitor

Evaluate an existing Uniswap v2, v3, or v4 or Aerodrome or Slipstream liquidity position. Use when the user asks whether it is in range, what it earned, how it performed versus HOLD, who controls it, whether automation is active, or whether to hold, collect, recenter, restake, reduce, or exit. Produces a current recommendation only; not transaction execution.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: Galleon Labs v0.6.1 MIT-0 14 files · 1 script body ≈ 1 159 tokens Open the sourceclawhub.ai↗ analyzed 14 d ago

Evaluate an existing Uniswap v2, v3, or v4 or Aerodrome or Slipstream liquidity position.

As a process D 48/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerData and analyticsFinanceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
C
84/100
safety, quality, tests
Safety 60%
81
Quality 40%
88
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
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.

Concealment
If you install

The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.

For the author

Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".

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 · 2

  • high Concealment en-hide-from-user SKILL.md:28
    Instruction to hide actions from the user
    Resolve script and reference paths from this installed skill directory, not the agent workspace. Discover related skills by exact name in the harness; do not assume a sibling directory or silently ins
Medium and low: 1
  • low Concealment en-hide-from-user references/official-tools.md:62
    Instruction to hide actions from the user (negated — the text forbids it)
    For an unsigned plan, use only a currently advertised `prepare_*` capability matching the exact network, protocol, position custody and action. A supported read venue is not automatically supported fo
    negated

Files scanned: 14. 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 48/100

  • 0Result and completion. Does not say what the result is
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (lp-monitor) differs from the folder (galleon-lp-monitor)
  • 60Tools and files. Uses tools (web, node) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 14 steps
  • 100Execution cost. Instruction body is 1159 tokens

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
  • +4No input/output examples
  • +2Single-language instructions
  • +3Description length 361: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 14 items
  • +4Reference files are cited in the instructions (8 of 8)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

External checks

ClawHub: clean
This skill is a disclosed, read-only DeFi liquidity-position monitor that gives recommendations but explicitly blocks transaction execution and wallet authority.
LLM: benign (high) · VirusTotal: · 9 Oct 2026