SKILLEMALL.ai

AB okx-onchain-gateway

Use this skill to 'broadcast transaction', 'send tx', 'estimate gas', 'simulate transaction', 'check tx status', 'track my transaction', 'get gas price', 'gas limit', 'broadcast signed tx', 'transaction hash confirmed on-chain', '交易哈希是否上链', '是否确认', or mentions broadcasting transactions, sending transactions on-chain, gas estimation, transaction simulation, tracking broadcast orders, or checking transaction status. Covers gas price, gas limit estimation, transaction simulation, transaction broadcasting, and order tracking across XLayer, Solana, Ethereum, Base, BSC, Arbitrum, Polygon, and 20+ other chains. Do NOT use for swap quote or execution - use okx-dex-swap instead. Do NOT use for general programming questions about transaction handling. Do NOT use when the user says only a single word like 'gas' or 'broadcast' without specifying a chain, transaction, or any other context.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 3 files body ≈ 4 135 tokens Open the sourcegithub.com analyzed 22 h ago

Use this skill to 'broadcast transaction', 'send tx', 'estimate gas', 'simulate transaction', 'check tx status', 'track my transaction', 'get gas price', 'gas…

As a process B 69/100 · Nearly there — weak spots: result and completion, running it twice

IntegrationGitHubCommercetype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
B
69/100
Nearly there
Result and completion w 14
0
Running it twice w 4
30
Tools and files w 18
60
the three weakest of ten parameters · all ten

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 · 0

    ✓ No critical or high findings

    Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note edit-residue the text marks something as outdated (lines 284): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 69/100

    • 0Result and completion. Does not say what the result is
    • 30Running it twice. 6 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4135 tokens
    • 85Steps. 60 steps, 1 vague phrases
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Progress reporting. Reports progress
    • low 15 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (4 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
    • +3Description length 889: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +4Structure: 24 headings
    • +3Step-by-step instructions: 60 items
    • +4Has examples (6 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.