BC ai-shifu-course-creator
Use when the user works with AI-Shifu (AI师傅) courses in any capacity of creating, writing, editing, rewriting, optimizing, reordering, deploying, publishing, previewing, or managing Teaching Prompts (per-lesson) and Course Prompts (course-level) — both written in MarkdownFlow (MDF). Covers the full course lifecycle — from converting raw material into structured lessons, to authoring interactions (single-select, multi-select, input, branching), adding variables, images, and course prompts, to deploying and managing live courses on the AI-Shifu platform. Also covers post-deployment analytics on those courses — learner count, completion rate, stuck lessons, orders, revenue, ratings, credit consumption, audience profiles, and individual learner tracking. Trigger on any mention of AI-Shifu, AI师傅, MarkdownFlow, Teaching Prompt, Course Prompt authoring, course analytics, creator analytics, 学习人数, 完成率, 卡课节, 订单收入, 积分消耗, or learner progress.
As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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 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".
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
- 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 Exfiltration
net-redirectable-api-keyscripts/shifu-cli.py:101Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
Files scanned: 40. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "version_management"
Process rating: all ten parameters 62/100
- 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
- 30Running it twice. 20 mutating operations with no state check
- 55Failures and branches. 1 branches
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 17 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2153 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)
- +3Description length 944: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- -34 of 4 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Structure: 5 headings
- +3Step-by-step instructions: 17 items
- +4Reference files are cited in the instructions (16 of 24)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.