SKILLEMALL.ai

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.

modbender/skill-library-mcp Agent Skills author: modbender MIT 8 files body ≈ 1 105 tokens Open the sourcegithub.com analyzed 2 d ago

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

GeneratorInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
95
Quality 40%
78
Run on models
none yet
Process rating
C
55/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. 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-token package-lock.json:31
    High-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-token package-lock.json:61
    High-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-token package-lock.json:73
    High-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-token package-lock.json:113
    High-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-token package-lock.json:122
    High-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-when description 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.