BB install-openviking-memory
Install and configure the OpenViking long-term memory plugin for OpenClaw via natural conversation. Once installed, the plugin automatically captures important facts from chats and recalls relevant context before each reply (auto-capture + auto-recall, cross-session). Covers prerequisites check, plugin install through OpenClaw's plugin manager first, with ov-install only as a backup path, wizard-based configuration, slot activation, gateway restart, verification, plus multi-tenant root-key support, multi-instance, and uninstall. Trigger when the user says any of: "install OpenViking", "set up memory", "configure memory plugin", "add long-term memory", "connect to OpenViking server", "RAG", "semantic memory", "帮我装 OpenViking", "配置记忆插件", "安装记忆功能", "接入 OpenViking", "我有一台 OpenViking 服务器". The user does NOT need to know any CLI commands — the agent runs everything and only asks for a few values. This skill assumes the OpenViking server is already running. If the server is not ready, the skill tells the user to contact their admin or set it up via the OpenViking docs — it does NOT install the server.
As a process B 71/100 · Nearly there — weak spots: result and completion, running it twice
How to improve
- Shorten the description to 1024 characters.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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
- error
description-longdescription is 1112 chars, limit 1024 - warning
body-longSKILL.md body ≈ 6941 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 71/100
- 0Result and completion. Does not say what the result is
- 30Running it twice. 13 mutating operations with no state check
- 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 6941 tokens
- 100Steps. 65 steps
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 25 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 20 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 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 1111: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +5Description quotes 11 example trigger phrases
- +4Structure: 42 headings
- +3Step-by-step instructions: 65 items
- +4Has examples (23 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 49.