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 flaqai/backlink_skills --skill backlink-source-prepgit clone --depth 1 https://github.com/flaqai/backlink_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/flaqai/backlink_skills/backlink-source-prep)<a href="https://agentmods.dev/skills/flaqai/backlink_skills/backlink-source-prep"><img src="https://agentmods.dev/badge/skills/flaqai/backlink_skills/backlink-source-prep/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/flaqai/backlink_skills/backlink-source-prep"><img src="https://agentmods.dev/badge/skills/flaqai/backlink_skills/backlink-source-prep.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 | $0.00059 | $0.00638 |
| Opus 5.5 | $0.00024 | $0.00255 |
| Sonnet 5.5 | $0.00012 | $0.00128 |
| Haiku 4.5 | $0.00006 | $0.00064 |
Grade A, and why
backlink-source-prep 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 27d 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
外链源表整理
把分散的竞品和外链导出整理成可追溯、可压缩、可继续筛选的标准源表。原始文件永不覆盖；所有派生文件另存。
三种模式
- 文件导入：用户已提供 CSV/XLSX，只做登记、读取和整理。
- 浏览器导出：只有得到明确授权才操作 Semrush；不使用爬虫替代产品导出。
- 离线整理：读取已有导出，生成合并候选、排除表、优先候选和统计报告。
需要浏览器导出时，先读 references/semrush-export.md。处理字段和压缩规则时，读 references/source-schema.md。
工作流程
- 为每个源文件登记目标域名、报告类型、数据库、报告日期、导出日期和文件名。
- 从自然搜索竞品中综合相关度、共同关键词、自然流量和主题适配选择参考竞品。指标决定优先顺序，不设单一严格淘汰线。
- 按工具允许的比较数量分批导出反向链接差异或引荐域名；记录批次号和竞品槽位。
- 运行
scripts/audit_semrush_exports.py检查文件数、行数、空表、表头差异和读取错误。 - 标准化目标域名、来源竞品和引荐域名；保留原始值与来源文件。
- 先排除自有域、竞品自身域、明显短链、赌博、恶意、镜像和没有研究价值的噪声，再生成优先候选。
- 输出总量、唯一域名数、目标覆盖数和各排除原因，不能只给压缩后的数字。
优先候选
优先级可以参考目标覆盖数、竞品覆盖数、链接实力、自然流量和主题信号，但不得把单个第三方分数当作最终质量结论。高权重通用站不自动成为可投递平台；低权重垂直目录也不自动淘汰。
交接
至少交付：原始文件登记、合并候选、排除表、优先候选、统计报告。文件名后缀应带数据量，例如 合并去重候选-<行数>条.csv。此阶段不得把结果写成“已找到外链平台”或“已核验可投递”。
What ships with it
4 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.
- 27d ago First seen · 35 lines · 59 tokens per session scan A b68a69d9e39a
backlink-source-prep is a skill published in the GitHub repository flaqai/backlink_skills (789 stars, last pushed today), licensed MIT. It adds 59 tokens to every session and 638 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-24.
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