SKILLEMALL.ai

BC Multi-Agent Safe-Cooperation (Single Device)

A single-device multi-Agent task chain collaboration methodology based on MGC. Through Master Agent orchestration, Script Agent scripting, and Executor Agent execution, achieves zero-exposure security collaboration for sensitive resources. Adapted to MGC 1.4.10.

ClawHub Agent Skills author: zkeviny v1.1.0 MIT-0 8 files body ≈ 2 579 tokens Open the sourceclawhub.ai analyzed 2 d ago

A single-device multi-Agent task chain collaboration methodology based on MGC.

As a process C 50/100 · Has gaps — weak spots: result and completion, failures and branches, consistency

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
C
50/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
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 · 0

✓ No critical or high findings

Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "spec"
  • note frontmatter-key unknown frontmatter key "id"
  • note frontmatter-key unknown frontmatter key "platform_compatibility"
  • note frontmatter-key unknown frontmatter key "changelog"

Process rating: all ten parameters 50/100

  • 0Result and completion. Does not say what the result is
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 40Consistency. Frontmatter name (Multi-Agent Safe-Cooperation (Single Device)) differs from the folder (mgc-task-chain-meta-skill-en)
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 36 steps, 1 vague phrases
  • 100Execution cost. Instruction body is 2579 tokens
  • 100Running it twice. No mutating operations
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 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)
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +2Single-language instructions
  • +3Description length 262: enough signal without eating the budget
  • +4Structure: 30 headings
  • +3Step-by-step instructions: 36 items
  • +4Has examples (8 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
This prompt-only skill is not overtly malicious, but it teaches agents to use sensitive local execution, credentials, persistence, and external-action workflows without enough scoping or confirmation.
LLM: suspicious (high) · 18 Aug 2026