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 sergekostenchuk/ui-ux-agent-skill-system --skill external-authority-placement-scoutgit clone --depth 1 https://github.com/sergekostenchuk/ui-ux-agent-skill-systemWrote 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/sergekostenchuk/ui-ux-agent-skill-system/external-authority-placement-scout)<a href="https://agentmods.dev/skills/sergekostenchuk/ui-ux-agent-skill-system/external-authority-placement-scout"><img src="https://agentmods.dev/badge/skills/sergekostenchuk/ui-ux-agent-skill-system/external-authority-placement-scout/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/sergekostenchuk/ui-ux-agent-skill-system/external-authority-placement-scout"><img src="https://agentmods.dev/badge/skills/sergekostenchuk/ui-ux-agent-skill-system/external-authority-placement-scout.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 | $0.00081 | $0.00679 |
| Opus 5 | $0.00041 | $0.00340 |
| Sonnet 5 | $0.00016 | $0.00136 |
| Haiku 4.5 | $0.00008 | $0.00068 |
Grade A, and why
external-authority-placement-scout 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.
This is a copy
97% identical to external-authority-placement-scout — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
External Authority Placement Scout
Use this skill only after the white-hat authority policy exists.
Read $HOME/SKILL/plans/seo-llm-skill-cluster/authority/white-hat-authority-policy.md
before creating an opportunity register.
Read references/scouting-workflow.md for candidate sources, required register fields, and draft rules.
Owns
- dry-run opportunity discovery;
- opportunity register rows;
- relevance and target-fit scoring;
- platform-rule checklist;
- approval-gated outreach or submission drafts;
- handoff to backlink-quality-validator.
Does Not Own
- external posting;
- account edits;
- PR creation;
- email/DM sending;
- buying links;
- spam automation;
- final quality validation after a link exists.
Workflow
- Define target site, target pages, audience, and allowed opportunity categories.
- Collect candidate opportunities from user-provided platforms or approved public research.
- Check relevance, user value, target fit, and policy risk.
- Record platform-rule status and whether current official/public rules must be rechecked.
- Create register rows matching the opportunity schema.
- Draft optional human-review text only when useful.
- Require explicit user approval before any external action.
- Hand off existing or proposed placements to
backlink-quality-validator.
Non-Negotiables
- Dry-run by default.
- Do not post links anywhere.
- Do not open PRs.
- Do not send outreach.
- Do not create accounts.
- Do not recommend PBNs, link farms, fake reviews, fake accounts, mass profile creation, hidden links, or irrelevant directories.
- Do not use exact-match anchor stuffing.
- Do not claim authority impact without evidence.
Safety And Privacy Boundaries
- Do not store platform credentials, private messages, contact lists, cookies, or tokens.
- Do not scrape platforms against their rules.
- Do not include private account data in reports.
- If the user approves a future external action, create a separate task with platform, draft, approval, rollback/removal path, and monitoring plan.
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.
- 12d ago First seen · 86 lines · 81 tokens per session scan A 9997ed3ca13b
external-authority-placement-scout is a skill published in the GitHub repository sergekostenchuk/ui-ux-agent-skill-system (23 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 81 tokens to every session and 679 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to external-authority-placement-scout, differing in 6 lines, and is treated as a copy.
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