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 Gingiris-1031/gingiris-skills --skill gr-competitor-researchgit clone --depth 1 https://github.com/Gingiris-1031/gingiris-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/gingiris-1031/gingiris-skills/gr-competitor-research)<a href="https://agentmods.dev/skills/gingiris-1031/gingiris-skills/gr-competitor-research"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/gr-competitor-research/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/gingiris-1031/gingiris-skills/gr-competitor-research"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/gr-competitor-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00582 | $0.02525 |
| Opus 5 | $0.00291 | $0.01262 |
| Sonnet 5 | $0.00116 | $0.00505 |
| Haiku 4.5 | $0.00058 | $0.00252 |
Grade A, and why
gr-competitor-research 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 236 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitor Research & Growth Flywheel Playbook — Full SOP
🌍 Language / 语言: 中文 | English | 日本語 | 한국어
Complete SOP for systematic competitor research: website evolution analysis, social media channel teardown, growth flywheel scoring, X/Twitter propagation chain mapping, and KOL identification. Battle-tested across 150+ AI startups. Includes Lovable full case study (Nov 2024 launch: 229K impressions, 4.3M video views, 10K+ Discord community).
一、竞品调研核心框架
1.1 四步调研法
| 步骤 | 内容 | 产出物 |
|---|---|---|
| Step 1 | 拆解竞品官网不同阶段版本 | 官网演变路径、Value Proposition演进、获客结构 |
| Step 2 | 拆解竞品社媒渠道内容策略 | 各渠道内容分类、发布节奏、KOL合作模式 |
| Step 3 | 导航站拆分（按需） | 导航站流量来源、友商投放入口 |
| Step 4 | 广告投放拆分（按需） | 投放渠道、素材策略、流量来源 |
1.2 工具清单
| 工具 | 用途 |
|---|---|
| Wayback Machine | 查看竞品历史官网快照 |
| SimilarWeb | 流量来源分析、渠道分布 |
| Semrush | SEO、广告投放分析 |
二、官网拆解方法论
2.1 三个关键版本节点
- 第一版本的官网 — 最小可行版本
- 第一阶段Beta Test的官网 — 封闭测试期
- 第一阶段正式Launch的官网 — 公开上市
2.2 每版本记录维度
| 维度 | 内容 |
|---|---|
| 一句话介绍 | 核心Value Proposition |
| 官网长度 | 总屏数、落地页结构 |
| 用户案例 | 行业/场景用例 |
| 框架结构 | Banner/Pricing/CTA |
| SEO动作 | 标题/描述变化 |
| 社区渠道 | Discord/Reddit启动节点 |
| 集成生态 | 第三方集成 |
2.3 对比表格模板
| 阶段 | 时间节点 | Value Prop | 官网长度 | 主要板块 | 启动渠道 | 关键Feature |
|---|---|---|---|---|---|---|
| V1 | YYYY-MM | ... | X屏 | ... | ... | ... |
| Beta | YYYY-MM | ... | X屏 | ... | ... | ... |
| Launch | YYYY-MM | ... | X屏 | ... | ... | ... |
三、社媒渠道内容拆解
3.1 流量来源判断
先用SimilarWeb判断主要流量来源，再针对重点渠道深入拆解。优先分析对应渠道做得好的竞品。
3.2 Twitter/X 账号矩阵
| 账号类型 | 拆解重点 |
|---|---|
| 官媒 | 发布频次/节奏/风格、内容分类比例 |
| 创始人账号 | 与官媒差异化程度 |
| Dev Rel账号 | BD/生态合作内容 |
| 红人账号 | 不同阶段KOL合作 |
3.3 内容发布节奏（四阶段）
内测（封闭测试）→ 大范围发布 → 长线运营 → Launch Week
3.4 各平台策略对比
| 维度 | X/Twitter | YouTube | TikTok | |
|---|---|---|---|---|
| 定位 | 传播引爆 | 用户激活 | 企业获客 | 破圈拉新 |
| 频率 | 每日1-3条 | 每周1-3条 | 每周1-2条 | 高 |
What ships with it
3 files 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.
- 9d ago First seen · 236 lines · 582 tokens per session scan A 1c7dec1615e6
gr-competitor-research is a skill published in the GitHub repository Gingiris-1031/gingiris-skills (79 stars, last pushed 4d ago), licensed MIT. It adds 582 tokens to every session and 2,525 once invoked, about $0.0029 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 2026-08-30.
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