BB knowledge-advisor
| A Knowledge Advisor that extracts, organizes, and applies knowledge from books and learning materials to real-world situations. Acts as a persistent consultant grounded STRICTLY in your ingested materials — every piece of advice cites the source book, chapter, and framework. Never gives advice from training data. Use when: ingesting a new book or material, seeking advice for a situation, searching your knowledge base, asking what your books say about a topic, checking knowledge base health, or managing your extracted knowledge. Trigger phrases: advise me, what do my books say, how should I handle, apply knowledge, ingest this book, search my knowledge base, based on my books, knowledge advisor, KB health, sync knowledge base, 根據我的書, 請教建議, 知識顧問. Supports: English, Traditional Chinese (繁體中文), Simplified Chinese (简体中文).
As a process B 67/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, progress reporting
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- 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
-
medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bashallowed-tools: Read Bash Glob Grep Write Edit WebFetch
Files scanned: 25. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "arguments"
Process rating: all ten parameters 67/100
- 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
- 60Result and completion. Output format stated, no completion criterion
- 70Failures and branches. 11 branches
- 85Steps. 140 steps, 1 vague phrases
- 100Tools and files. Tools declared in frontmatter
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2763 tokens
- 100Running it twice. Mutating operations check current state
- low 19 top-level sections: this looks like several domains in one skill
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)
- +3Description length 830: 120–800 characters recommended
- +4No input/output examples
- -31 of 3 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Structure: 20 headings
- +3Step-by-step instructions: 140 items
- +3Output format is stated explicitly
- +4Reference files are cited in the instructions (9 of 9)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.