BC vibetrading-global-signals
Query AI-generated trading signals from vibetrading-datahub. Signals are produced by autonomous agents analyzing whale activity, news, funding rates, and technical indicators.
Query AI-generated trading signals from vibetrading-datahub.
As a process C 55/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 5
✓ No critical or high findings
Medium and low: 5
-
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:31High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…9dM/mwVgvbZJaSNaRk+bshk…Kbz+IoId…W0Q==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:61High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…SDq+2kAA…MOe/+5cdoEdg==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:73High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…GLw+xYSd…cqA==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:113High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…FrF+LTRo…W3g==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:122High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…A6j+hAmM…GbS+kf5c…csw==",
detector
Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 55/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 85Steps. 29 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1105 tokens
- low 10 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 175: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 29 items
- +3Output format is stated explicitly
- +4Has examples (7 code blocks)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.