BB xingtu-task-invite-code
This skill should be used when the user needs to batch download QR code invitation images from XingTu (星图) recruitment tasks. It automates the full workflow: cookie authentication, fetching the task list from the XingTu platform via provider_get_task_order_list API, paginating through all tasks, navigating to each task detail page, clicking 邀约达人 then 二维码邀请 then 下载图片, and saving the QR code images to D:\xingtu\task-invite\{{task_id}}. Trigger phrases include: 星图邀约码, 批量下载邀约二维码, 星图任务二维码, 下载星图邀约图片, xingtu invite code, 星图任务邀请, provider_get_task_order_list invite.
This skill should be used when the user needs to batch download QR code invitation images from XingTu (星图) recruitment tasks.
As a process B 71/100 · Nearly there — weak spots: result and completion
How to improve
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: This skill should be used when the user needs to batch download QR… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
body-longSKILL.md body ≈ 7603 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 71/100
- 0Result and completion. Does not say what the result is
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 7603 tokens
- 85Steps. 79 steps, 1 vague phrases
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 5 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 12 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)
- +3Output format is not stated: the model decides each time
- -4Absolute local paths (C:\Users, /home/…): not portable
- -41 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +3Description length 564: enough signal without eating the budget
- +4Structure: 52 headings
- +3Step-by-step instructions: 79 items
- +4Has examples (32 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.