SKILLEMALL.ai
GitHub ↗ RU Sign in

BC shared-memory

Set up shared memory between multiple OpenClaw agents so they stay in sync without the user repeating context. Use when a user has 2+ agents (workspaces) and wants them to share knowledge, sync conversation summaries, and maintain a common long-term memory. Also use when user asks about multi-agent setup, agent sync, or says things like "stop repeating myself to different agents".

ClawHub Agent Skills author: junweiren98-rgb v1.1.0 MIT-0 2 files body ≈ 1 295 tokens Open the sourceclawhub.ai↗ analyzed 5 d ago

Set up shared memory between multiple OpenClaw agents so they stay in sync without the user repeating context.

As a process C 60/100 · Has gaps — weak spots: result and completion, consistency, running it twice

ProcedureAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Running it twice w 4
30
Consistency w 8
40
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: 2. 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 60/100

    • 0Result and completion. Does not say what the result is
    • 30Running it twice. 6 mutating operations with no state check
    • 40Consistency. Frontmatter name (shared-memory) differs from the folder (multi-agent-shared-memory)
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 18 steps
    • 100Execution cost. Instruction body is 1295 tokens
    • 100Progress reporting. Reports progress

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 383: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 18 items
    • +4Has examples (7 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: suspicious
    This skill has a coherent shared-memory purpose, but it makes persistent cross-workspace agent-instruction and memory changes without enough consent, scoping, or rollback controls.
    LLM: suspicious (high) · VirusTotal: · 11 Sept 2026