AD partner-selection
当用户需要为某个目标国家寻找、筛选或评估本地电子发票合规通道合作伙伴时，使用本 Skill。 覆盖场景：识别和筛选本地 e-invoicing 接入点（AP/SP/T-VAN/ASP/PJAP/SDI中间商）合作伙伴、 评估候选方是否适合作为我方的白标底层通道、对候选方开展多轮过滤和反向证伪、 设计POC验收方案、制定商业谈判框架。 触发信号（中文）：用户提到"找电子发票合作伙伴""找电子发票通道商""找本地AP""找T-VAN""找接入方""谁做底层""通道选型"， 或在完成某国市场评估后询问"怎么接入""找谁合作""落地路径"。 触发信号（English）：user mentions "find e-invoice local partner", "access point selection", "e-invoice channel partner for [country]", "who to work with for e-invoicing in [country]", “e-invoice partner evaluation", "POC design for [country]". 不要在以下场景触发：用户只是询问某国电子发票法规概览但不涉及合作伙伴筛选、用户要求做市场准入评估报告但未明确涉及合作伙伴选型。 本 Skill 输出完整的推导过程，每一轮过滤都可追溯，最终给出分梯队推荐清单和落地谈判建议。
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
The same skill appears in 1 more place: ClawHub
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 · 0
✓ No critical or high 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 49/100
- 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
- 40Consistency. Frontmatter name (partner-selection) differs from the folder (e-invoice-partner-selection)
- 100Tools and files. No external tools needed
- 100Steps. 47 steps
- 100Execution cost. Instruction body is 2236 tokens
- 100Running it twice. No mutating operations
- low 18 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 10 example trigger phrases
- +3Description length 619: enough signal without eating the budget
- +4Structure: 39 headings
- +3Step-by-step instructions: 47 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.