SKILLEMALL.ai

AC Agent Swarm Network

Agent communication protocol skill. Provides: inter-agent messaging, context snapshot/restore, event-driven collaboration, model dispatch notifications, sub-agent management, task routing, file transfer, and network diagnostics. Invoke this Skill when cross-session context persistence, multi-agent coordination, or context overflow handling is needed. Built on top of Pilot Protocol (https://github.com/TeoSlayer/pilotprotocol).

ClawHub Agent Skills author: KELIHAO v1.0.6 5 files body ≈ 3 385 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, consistency

AnalyzerGitHubAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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 · 0

    ✓ No critical or high findings

    Files scanned: 5. 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)

    Process rating: all ten parameters 51/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 27 mutating operations with no state check
    • 40Consistency. Frontmatter name (Agent Swarm Network) differs from the folder (agent-swarm-network)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (write, node) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 26 steps
    • 100Execution cost. Instruction body is 3385 tokens
    • low 17 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 429: enough signal without eating the budget
    • +4Structure: 46 headings
    • +3Step-by-step instructions: 26 items
    • +4Has examples (20 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

    External checks

    ClawHub: suspicious
    This is a disclosed agent networking and memory skill, but it automatically stores and restores unencrypted session context that may include secrets.
    LLM: suspicious (high) · VirusTotal: suspicious · 28 May 2026