AC hypernatt-liq-radar
Instructs the agent to call the remote HyperNatt MCP tool get_liq_radar (forced-order / liquidation map) before sizing any crypto perp - BTC ETH SOL and other whitelist assets, any venue. Docs + call order only - no local exec/shell/files. This skill covers market-data tools only (manifest + liq radar). Not trade advice. get_liq_radar = $0.001 USDC via x402.
Instructs the agent to call the remote HyperNatt MCP tool getliqradar (forced-order / liquidation map) before sizing any crypto perp - BTC ETH SOL and other…
As a process C 50/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 360 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "permissions"
Process rating: all ten parameters 50/100
- 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
- 50When it triggers. No condition that starts the skill
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Consistency. The Hermes dialect needs category and tags
- 85Steps. 10 steps, 1 vague phrases
- 100Execution cost. Instruction body is 714 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +3Description length 360: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 10 items
- +4Has examples (1 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.