SKILLEMALL.ai

AC use-hln-api

Consult & operate against the Hyperliquid Names API. Use when your agent needs to resolve `.hl` names, reverse-resolve addresses, fetch HLN profiles or records, inspect owner or list queries, diagnose HLN API failures, prepare a mint-pass request, or guide HyperEVM dApp integration with HL Names.

ClawHub Agent Skills author: HL Names v1.0.0 MIT-0 19 files · 3 scripts body ≈ 1 673 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationGitHubAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
96
Quality 40%
84
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • low Exfiltration read-dotenv env-example.txt:4
      Reads a .env file (test fixture / example file)
      #   cp .env.example .env
      fixture
    • low Exfiltration read-dotenv env-example.txt:6
      Reads a .env file (test fixture / example file)
      #   source .env
      fixture
    • low Exfiltration read-dotenv README.md:45
      Reads a .env file
      cp .env.example .env
    • low Secrets in code secret-high-entropy-token references/integration.md:12
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - `0xF2…652`
      quoted

    Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 64/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 6 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 48 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1673 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 297: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 48 items
    • +4Has examples (0 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This skill is a disclosed HL Names API helper; it makes external API calls and includes a public fallback API key, so users should avoid sensitive lookups or proprietary eval data.
    LLM: benign (high) · VirusTotal: · 29 May 2026