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AC ocmemog-installer

Install and configure ocmemog, the OpenClaw durable memory plugin and sidecar. Use when a user asks to install ocmemog, set up durable memory, improve OpenClaw memory, enable transcript-backed continuity, configure the ocmemog sidecar, reinstall/update ocmemog, or troubleshoot its install. Prefer the public package install path first; fall back to the GitHub repo installer path when package install is unavailable or source checkout is explicitly desired.

ClawHub Agent Skills author: simbimbo v0.1.8 MIT-0 3 files · 1 script body ≈ 917 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureGitHubInfrastructureCommercetype 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
A
93/100
safety, quality, tests
Safety 60%
99
Quality 40%
85
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Dangerous commands cmd-background-process scripts/install-ocmemog.sh:32
      Starts a background / autostarted process
      nohup "$REPO_DIR/scripts/ocmemog-sidecar.sh" >"$REPO_DIR/.ocmemog-sidecar.log" 2>&1 &

    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 53/100

    • 0Result and completion. Does not say what the result is
    • 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. 3 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 100Steps. 37 steps
    • 100Failures and branches. 12 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 917 tokens

    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 458: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 37 items
    • +4Has examples (1 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: suspicious
    This installer is purpose-aligned, but it can run changing remote code, alter OpenClaw memory settings, and leave a local memory service running.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026