BD linkfox-tiktok-creator
TikTok 达人（Creator/affiliate creator）数据与可购物视频技能，经 LinkFox 网关代理调用 TikTok Shop 达人开放接口：达人主页/档案、达人绑定店铺商品、橱窗商品、可购物视频的上传/内容预检/发布/发布状态查询。需要达人 access_token（user_type=1），由 linkfox-tiktok-video-auth 完成达人授权后取得。当用户提到 TikTok 达人、TikTok creator、达人主页、达人档案、达人资料、达人店铺商品、达人绑定店铺商品、达人橱窗商品、showcase 商品、上传可购物视频、发布可购物视频、视频发布状态、视频内容预检、shoppable video、affiliate creator、TikTok 带货达人信息、TikTok creator profile、shop products、showcase products、post shoppable video、video status、precheck 时触发此技能。即使用户未写 EHunt/紫鸟，只要需求是查 TikTok Shop 达人的资料、绑定商品或可购物视频带货操作，也应触发。**不含达人授权**（授权请用 linkfox-tiktok-video-auth）。
TikTok 达人（Creator/affiliate creator）数据与可购物视频技能，经 LinkFox 网关代理调用 TikTok Shop 达人开放接口：达人主页/档案、达人绑定店铺商品、橱窗商品、可购物视频的上传/内容预检/发布/发布状态查询。需要达人…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 3
✓ No critical or high findings
Medium and low: 3
-
low Secrets in code
secret-high-entropy-tokenscripts/onboarding.py:49High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)or "eyJh…iJ9")
quoted
A further 2 matches are quotations in this security skill's documentation and are not counted as findings.
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 46/100
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 34 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1344 tokens
- 100Running it twice. No mutating operations
- low The response is described with custom markup (7 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
- +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
- +4No input/output examples
- -31 of 2 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 566: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 34 items
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.