BF meituan-fenxiao-promotion-coupon
【美团专属大额券 + 一键直达短链路 + 自动提醒长收益】 核心功能： ① 领券超便捷 —— 覆盖吃喝玩乐全场景，点一下就能领，领完马上用，无需等待； ② 优惠早知道 —— 每日热点活动一手掌握，专属链接直达，抢券快人一步； ③ 省钱自动化 —— 设置一次，每天自动提醒你领券，再也不怕错过任何福利。 触发词（共44个）： 【通用领券44个】领券、领优惠、领红包、领取优惠、我要领券、我要领优惠、帮我领券、帮我领红包、领取红包、领取优惠券、领取美团券、领美团红包、领美团优惠、美团发券、美团领券、美团红包、美团优惠券、美团超级红包、美团专属红包、美团大额券、美团神券、美团隐藏券、美团隐藏优惠、美团福利、美团羊毛、美团薅羊毛、薅美团羊毛、美团省钱、美团怎么省钱、美团有什么优惠、美团有没有券、美团有红包吗、美团优惠怎么领、今天有什么优惠、今日优惠、今日红包、优惠券、美团券、美团优惠、薅羊毛、福利、羊毛、今日活动、今天有什么活动 skill-version: 1.0.1 | clawhub-slug: meituan-fenxiao-promotion-coupon
As a process F 28/100 · Will not run — References files that are not bundled: activity_link
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 10. 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") - warning
missing-refreference to a missing file: activity_link
Process rating: all ten parameters 28/100
- 0Tools and files. 1 referenced file(s) missing: activity_link
- 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. 3 mutating operations with no state check
- 40Consistency. Frontmatter name (meituan-fenxiao-promotion-coupon) differs from the folder (meituan-union-coupon-skill)
- 100Steps. 66 steps
- 100Execution cost. Instruction body is 3020 tokens
- low 10 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
- -231 emoji in the instructions: noise for the model
- -33 of 5 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 484: enough signal without eating the budget
- +4Structure: 32 headings
- +3Step-by-step instructions: 66 items
- +4Has examples (17 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.