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 CHENyiru3/AI-Skills-Collections --skill page-keepergit clone --depth 1 https://github.com/CHENyiru3/AI-Skills-CollectionsWrote 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/chenyiru3/ai-skills-collections/page-keeper)<a href="https://agentmods.dev/skills/chenyiru3/ai-skills-collections/page-keeper"><img src="https://agentmods.dev/badge/skills/chenyiru3/ai-skills-collections/page-keeper/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/chenyiru3/ai-skills-collections/page-keeper"><img src="https://agentmods.dev/badge/skills/chenyiru3/ai-skills-collections/page-keeper.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 | $0.00101 | $0.01523 |
| Opus 5.5 | $0.00040 | $0.00609 |
| Sonnet 5.5 | $0.00020 | $0.00305 |
| Haiku 4.5 | $0.00010 | $0.00152 |
Grade A, and why
page-keeper 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 6d 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 — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Page Keeper
page-keeper is a meta-skill. Its job is not to directly maintain the website. Its job is to inspect a website repo, extract structure and rules, ask only the missing high-value questions, and then generate a repo-specific maintenance skill for that site.
Optimize for personal websites generally. Be especially alert to academic and tech personal-site patterns such as publications, CVs, profile sections, project pages, news, downloadable assets, and repo-specific formatting contracts.
What To Produce
Always work toward these outputs, in order:
Repo assessmentDiscovered rulesQuestions for the userConfirmed rulesRulebookRepo-specific maintenance skill outlineFinal downstream SKILL.md draftSuggested eval prompts
Do not jump directly to the downstream skill.
Default Workflow
1. Inspect the repo first
Start with repo exploration, not questions.
Identify:
- framework and stack
- route pages and entrypoints
- layouts, templates, includes, or shared components
- data files and config files
- content directories for homepage, projects, publications, CV, blog/news, and personal pages
- repeated renderers and duplication patterns
- file naming and versioning conventions
- special logic for publications, references, CVs, downloadable files, and profile metadata
Use references/repo-discovery-checklist.md as the inspection checklist.
2. Build a repo map
Summarize the repo in a compact map with:
- framework
- main routes/pages
- content sources
- shared renderers
- configuration sources
- data-driven sections
- section duplication risks
- special derived-value rules such as dates, versions, or filenames
3. Split inferred rules from user-only rules
Always classify findings into two buckets.
Inferred from repo
Infer these directly when possible:
- framework and layout chain
- section inventory
- where content lives
- shared partials or includes
- rendering order and grouping
- bibliography or CV logic
- asset naming conventions
- duplication and centralization patterns
- existing tone and formatting patterns
What ships with it
6 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.
- 6d ago First seen · 207 lines · 101 tokens per session scan A 57f6c20d170e
page-keeper is a skill published in the GitHub repository CHENyiru3/AI-Skills-Collections (1 stars, last pushed 7d ago), licensed MIT. It adds 101 tokens to every session and 1,523 once invoked, about $0.0004 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 2026-10-02.
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