SKILLEMALL.ai

AD agent-relay

Cross-agent context sharing via shared files. Agents write trends, highlights, and signals to a shared folder. Other agents read before acting — creating coordinated behavior without direct messaging. Use when: multi-agent setups need coordination, agents should know what other agents found, trends from one source should influence another agent's actions. NOT for: real-time communication, agent-to-agent chat, single-agent setups.

ClawHub Agent Skills author: Gum97 v1.0.0 MIT-0 3 files body ≈ 575 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 37/100 · Unfinished process — weak spots: steps, result and completion, inputs and preconditions

GeneratorAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
D
37/100
Unfinished process
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
0
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 37/100

    • 0Steps. Prose only: no discrete steps
    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 40Consistency. Frontmatter name (agent-relay) differs from the folder (agent-shared-context)
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Execution cost. Instruction body is 575 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
    • +3No numbered steps or checklist
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 436: enough signal without eating the budget
    • +4Structure: 11 headings
    • +4Has examples (6 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: clean
    This skill transparently stores local shared notes so multiple agents can coordinate, with no evidence of network access, credential use, or hidden behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026