SKILLEMALL.ai
GitHub ↗ RU Sign in

BF 0xarchive

Query historical crypto market data from 0xArchive across Hyperliquid, Lighter.xyz, and HIP-3. Covers orderbooks, trades, candles, funding rates, open interest, liquidations, and data quality. Use when the user asks about crypto market data, orderbooks, trades, funding rates, or historical prices on Hyperliquid, Lighter.xyz, or HIP-3.

modbender/skill-library-mcp Claude Code author: modbender MIT 1 file body ≈ 3 714 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Query historical crypto market data from 0xArchive across Hyperliquid, Lighter.xyz, and HIP-3. Covers orderbooks, trades, candles, funding rates, open…

As a process F 52/100 · Will not run — References files that are not bundled: scripts/web3_subscribe.py

IntegrationData and analyticsWriting and documentsCustomer supporttype 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
76/100
safety, quality, tests
Safety 60%
73
Quality 40%
81
Run on models
none yet
Process rating
F
52/100
Will not run
References files that are not bundled: scripts/web3_subscribe.py
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. The text references files that are not there: add them or drop the references.
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

✓ No critical or high findings

Medium and low: 7
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash
  • medium Exfiltration net-credential-use SKILL.md:211
    Credential used in a network call (verify the destination is the intended service)
    curl -s -H "x-api-key: $OXARCHIVE_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:215
    Credential used in a network call (verify the destination is the intended service)
    curl -s -H "x-api-key: $OXARCHIVE_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:244
    Credential used in a network call (verify the destination is the intended service)
    curl -s -H "x-api-key: $OXARCHIVE_API_KEY" \
  • medium Exfiltration net-credential-use SKILL.md:248
    Credential used in a network call (verify the destination is the intended service)
    curl -s -H "x-api-key: $OXARCHIVE_API_KEY" \
  • low Exfiltration net-credential-use SKILL.md:22
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    curl -s -H "x-api-key: $OXARCHIVE_API_KEY" "https://api.….io/v1/..."
    vendor-host
  • low Secrets in code secret-high-entropy-token SKILL.md:158
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - Domain: `{ name: "USD Coin", version: "2", chainId: 8453, verifyingContract: "0x83…913" }`
    quoted

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/web3_subscribe.py

Process rating: all ten parameters 52/100

Will not run. References files that are not bundled: scripts/web3_subscribe.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/web3_subscribe.py
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 1 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 7 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3714 tokens
  • low 11 top-level sections: this looks like several domains in one skill

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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 336: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 7 items
  • +3Output format is stated explicitly
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.