SKILLEMALL.ai

CC lp-plan

Design or backtest an exact unsigned liquidity plan for a chosen Uniswap v2, v3, or v4 or Aerodrome or Slipstream pool. Use when the user asks for position size, token amounts, range or ticks, historical range performance, fee tier, staking route, approvals, slippage limits, deadlines, transaction order, or preflight checks. Planning only; not for selecting an unassessed pool, signing, or submitting.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: Galleon Labs v0.6.1 MIT-0 17 files · 2 scripts body ≈ 1 623 tokens Open the sourceclawhub.ai↗ analyzed 14 d ago

Design or backtest an exact unsigned liquidity plan for a chosen Uniswap v2, v3, or v4 or Aerodrome or Slipstream pool.

As a process C 62/100 · Has gaps — weak spots: result and completion, failures and branches, consistency

ProcedureSoftware developmentData and analyticsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
83/100
safety, quality, tests
Safety 60%
81
Quality 40%
86
Run on models
none yet
Process rating
C
62/100
Has gaps
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:31
    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: 17. 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 62/100

  • 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
  • 40Consistency. Frontmatter name (lp-plan) differs from the folder (galleon-lp-plan)
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 100Steps. 15 steps
  • 100When it triggers. States when to use and when not to
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Execution cost. Instruction body is 1623 tokens
  • 100Running it twice. No mutating operations

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
  • +4No input/output examples
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 403: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 15 items
  • +4Reference files are cited in the instructions (10 of 10)
  • +1License stated

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

External checks

ClawHub: clean
This skill is a disclosed DeFi liquidity-planning helper that produces unsigned plans and review links, not signatures or submitted transactions.
LLM: benign (high) · VirusTotal: · 9 Oct 2026