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AB huawei-cloud-openviking-agent-integration

Integrate and unbind OpenViking long-term memory with coding agents. Supports 8 agents (CodeArts CLI, OpenCode, OpenClaw, Hermes, WorkSwarm, KimiCode, DeepSeek Harness, Prime Agent) via their native mechanism — MCP, HTTP memory provider, TypeScript extension hooks, or settings.json config. Both integration and unbinding require explicit user authorization. Use this skill when the user wants to: (1) integrate OpenViking memory into a coding agent, (2) unbind OpenViking from a coding agent, (3) check the integration status of all agents, (4) verify the OpenViking MCP endpoint, (5) rebuild the OpenClaw sandbox to apply template changes. Trigger words: "OpenViking integration", "agent memory binding", "MCP setup", "OpenViking MCP", "integrate OpenViking", "unbind OpenViking", "记忆集成", "记忆解绑", "OpenViking 集成", "OpenViking 解绑", "agent long-term memory", "context database".

ClawHub Agent Skills author: huaweicloud-skills-team v1.0.2 MIT-0 27 files · 19 scripts body ≈ 1 452 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Integrate and unbind OpenViking long-term memory with coding agents.

As a process B 71/100 · Nearly there — weak spots: result and completion, progress reporting

IntegrationGitHubData and analyticsAI 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
A
90/100
safety, quality, tests
Safety 60%
94
Quality 40%
85
Run on models
none yet
Process rating
B
71/100
Nearly there
Progress reporting w 2
0
Result and completion w 14
40
Failures and branches w 10
50
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • medium Exfiltration exfil-read-secret-files scripts/agents/opencode.sh:222
      Reads credential / secret files (quoted — discussed, not commanded)
      cat > "$HOME/.npmrc" <<'NPMRC'
      quoted
    • low Dangerous commands cmd-autorun-instruction SKILL.md:86
      Instructs the agent to auto-run a script on every session (documentation of a security skill)
      - **Do not fabricate integration state** — always run `status.sh` to verify before reporting.
      security skill

    Files scanned: 27. 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 71/100

    • 0Progress reporting. Says nothing while it works
    • 40Result and completion. Does not say what the result is
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web) 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. 14 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1452 tokens
    • 100Running it twice. Mutating operations check current state
    • low 10 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (10 tags): a typed call is more reliable

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 878: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -2localhost URLs: will not work for another user
    • -32 of 6 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 10 example trigger phrases
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 14 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (5 of 5)

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

    External checks

    ClawHub: suspicious
    This skill has a coherent OpenViking memory-integration purpose, but it makes persistent agent changes while relying on mutable remote code and unsafe endpoint handling.
    LLM: suspicious (high) · 11 Sept 2026