Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ilexlyu/ad-proposal-skills --skill ad-insight-reviewergit clone --depth 1 https://github.com/ilexlyu/ad-proposal-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ilexlyu/ad-proposal-skills/ad-insight-reviewer)<a href="https://agentmods.dev/skills/ilexlyu/ad-proposal-skills/ad-insight-reviewer"><img src="https://agentmods.dev/badge/skills/ilexlyu/ad-proposal-skills/ad-insight-reviewer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ilexlyu/ad-proposal-skills/ad-insight-reviewer"><img src="https://agentmods.dev/badge/skills/ilexlyu/ad-proposal-skills/ad-insight-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00080 | $0.00575 |
| Opus 5 | $0.00040 | $0.00287 |
| Sonnet 5 | $0.00016 | $0.00115 |
| Haiku 4.5 | $0.00008 | $0.00057 |
Grade A, and why
ad-insight-reviewer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
洞察生成与评审
目标：从事实里提炼有立场的策略判断。洞察不是事实复述，而是对事实的重新解释。
Inputs
- 资料表或事实清单。
- 产品卖点、目标用户、客户诉求、竞争环境。
- 如果资料不足，先列“需要补证据的问题”，不要强行产出结论。
Workflow
- 事实分组：用户、人群、品类、竞品、渠道、文化情绪、购买阻力。
- 寻找张力：新旧变化、说法与行为不一致、用户想要但不愿承认、竞品都忽略的角度。
- 生成候选洞察：输出 10 条，每条必须是判断句。
- 逐条评分：按 4 个维度评分 1-5。
- 选择 Top 3：说明为什么值得客户相信，以及会改变什么动作。
Scoring Dimensions
| 维度 | 问题 |
|---|---|
| 重新解释事实 | 它是否不是事实复述，而是给事实换了一个解释？ |
| 明确立场 | 它是否允许被反驳，而不是永远正确的废话？ |
| 行动影响 | 它是否能改变产品定位、传播方向或渠道选择？ |
| 证据/反证 | 它是否有证据支撑，也看过可能反驳？ |
Output Format
## 候选洞察 10 条
| 洞察 | 支持事实 | 可能反证 | 行动影响 | 评分 |
## 推荐 Top 3
### 1. 洞察
- 策略句：
- 为什么成立：
- 客户为什么会相信：
- 会改变的动作：
- 风险：
Quality Bar
- 禁止输出“年轻人越来越注重情绪价值”“消费者更关注健康”等事实复述。
- 必须改写成有判断的策略句，例如“消费者不是更关注健康，而是更害怕自己看起来不健康”。
- 说明候选项为何只是事实复述，或为何足以成为能改变行动的策略判断。
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 53 lines · 80 tokens per session scan A 224097c1b29b
ad-insight-reviewer is a skill published in the GitHub repository ilexlyu/ad-proposal-skills (10 stars, last pushed 1mo ago), licensed MIT. It adds 80 tokens to every session and 575 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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