Front-End Checklist is a collection of front-end web development rules organized as a practical review and quality workflow for people and AI agents. Developers use it to audit projects and pull requests, check implementation details, and find guidance for remediation and verification. The catalogue entries provide skills, instructions, MCP tools, and a plugin for using the checklist in agent workflows.
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 thedaviddias/Front-End-Checklist --skill freshnessgit clone --depth 1 https://github.com/thedaviddias/Front-End-ChecklistWrote 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/thedaviddias/front-end-checklist/freshness)<a href="https://agentmods.dev/skills/thedaviddias/front-end-checklist/freshness"><img src="https://agentmods.dev/badge/skills/thedaviddias/front-end-checklist/freshness/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/thedaviddias/front-end-checklist/freshness"><img src="https://agentmods.dev/badge/skills/thedaviddias/front-end-checklist/freshness.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 | $0.00040 | $0.00668 |
| Opus 5.5 | $0.00016 | $0.00267 |
| Sonnet 5.5 | $0.00008 | $0.00134 |
| Haiku 4.5 | $0.00004 | $0.00067 |
Grade A, and why
freshness 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 23d 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Show content freshness signals
Google's Query Deserves Freshness (QDF) algorithm boosts recent or recently updated content for time-sensitive queries. Missing or stale freshness signals mean your updated content competes without the freshness advantage it deserves.
Quick Reference
- Set the
Last-ModifiedHTTP response header and includedateModifiedin Article JSON-LD on all content pages - Update
dateModifiedonly when content substantively changes — trivial edits should not alter the date - For time-sensitive topics (news, tutorials, product reviews), freshness directly influences Google's ranking of your content
Check
For each article or blog page: (1) Check the HTTP response Last-Modified header — is it set and recent? (2) Check the JSON-LD for a dateModified property in ISO 8601 format. (3) Is a visible 'Last updated' date shown to users? (4) Is the dateModified in JSON-LD consistent with the visible date and the Last-Modified header?
Fix
- Configure your web server to send
Last-Modifiedheaders based on the file modification time:- Nginx:
add_header Last-Modified $date_gmt; - Apache: ensure
mod_headersis enabled; static files serve Last-Modified automatically.
- Nginx:
- Update Article JSON-LD to include
dateModified:{ "@type": "Article", "dateModified": "2024-11-20T14:30:00Z" } - Add a visible "Last updated" date to the article template.
- Hook your CMS to update
dateModifiedonly when content is substantively changed (not on metadata-only saves). - If using a static site generator (Next.js, Astro), pass the frontmatter
updatedAtfield through to the JSON-LD and<time>elements.
Explain
Google's freshness algorithm (QDF — Query Deserves Freshness) actively boosts recently published or updated content for searches where recency matters. If your dateModified is stale or absent, Google may not credit your content with the freshness it deserves, ranking older competitors above you even after you have updated the article.
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.
- 23d ago Changed d89b519ec84d
- 1mo ago First seen · 55 lines · 40 tokens per session scan A 095dc38514fa
freshness is a skill published in the GitHub repository thedaviddias/Front-End-Checklist (74,577 stars, last pushed 21d ago), licensed MIT. It adds 40 tokens to every session and 668 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 2026-09-03.
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