AD bailian_faiss_kb
使用 Python、FAISS、BM25、阿里云百炼 text-embedding-v4 与可选的 qwen3-rerank，维护基于文件目录的本地知识库；适用于在 OpenClaw 预先抽取文本后，遍历 chunks 与 T2Q 建立索引，以及对指定知识库或全部知识库做综合、语义或关键词查询。
As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
ProcedureInfrastructureAI and agentsSoftware developmenttype and topics are labelled automatically from the skill text
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 39/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (bailian_faiss_kb) differs from the folder (rag-kb)
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100Steps. 103 steps
- 100Execution cost. Instruction body is 1920 tokens
- low 10 top-level sections: this looks like several domains in one skill
- low The skill ranks results itself: that belongs to the system behind the tool, not the model
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 148: enough signal without eating the budget
- +4Structure: 22 headings
- +3Step-by-step instructions: 103 items
- +4Has examples (17 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.
External checks
ClawHub: clean
This is a disclosed knowledge-base indexing and search skill that stores files locally and uses Alibaba Cloud for its advertised embedding and reranking features.
LLM: benign (high) · VirusTotal: · 29 May 2026