stock-ai-newsletter: Skill for Claude Code

.agents/skills/programmatic-seo/SKILL.md

programmatic-seo is a skill for Claude Code, Codex from MongLong0214/stock-ai-newsletter. It costs 85 tokens per session (3,854 once invoked), scanned A, original, no licence file.

A method for creating many search-engine pages from templates and data, such as location, directory, comparison, or integration pages.

In plain words
What is it for?
It helps build pages at scale for searches such as a service plus a city, or a comparison between products.
Why use it?
It avoids writing each SEO page from scratch while keeping pages based on consistent patterns and information.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing. Also seen: installed under .agents/ (shared by several agents).

This is MongLong0214/stock-ai-newsletter's own configuration. It tells Claude Code and Codex how to work on stock-ai-newsletter itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything stock-ai-newsletter configures →

Reuse

Borrowing it

Nothing to install: this file belongs to MongLong0214/stock-ai-newsletter. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/MongLong0214/stock-ai-newsletter/main/.agents/skills/programmatic-seo/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/MongLong0214/stock-ai-newsletter

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for programmatic-seo

README.md
[![agentmods](https://agentmods.dev/badge/skills/monglong0214/stock-ai-newsletter/programmatic-seo/github.svg)](https://agentmods.dev/skills/monglong0214/stock-ai-newsletter/programmatic-seo)
Your own site
<a href="https://agentmods.dev/skills/monglong0214/stock-ai-newsletter/programmatic-seo"><img src="https://agentmods.dev/badge/skills/monglong0214/stock-ai-newsletter/programmatic-seo/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.

agentmods 80×15 button for programmatic-seo

Your own site · 80×15
<a href="https://agentmods.dev/skills/monglong0214/stock-ai-newsletter/programmatic-seo"><img src="https://agentmods.dev/badge/skills/monglong0214/stock-ai-newsletter/programmatic-seo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,854 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00085 $0.03854
Opus 5.5 $0.00034 $0.01542
Sonnet 5.5 $0.00017 $0.00771
Haiku 4.5 $0.00009 $0.00385

Measured 2mo ago against content hash f54fd1731b67, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

programmatic-seo 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 2mo 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.

.agents/skills/programmatic-seo/SKILL.md · 627 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

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.

  1. 2mo ago First seen · 627 lines · 85 tokens per session scan A f54fd1731b67

Subscribe to this mod's changes

programmatic-seo is a skill published in the GitHub repository MongLong0214/stock-ai-newsletter (0 stars, last pushed 2d ago), with no licence file. It adds 85 tokens to every session and 3,854 once invoked, about $0.0003 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 2026-08-31.

Related

programmatic-seo compared with skills from other repositories

programmatic-seo next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
programmatic-seoMongLong0214/stock-ai-newsletterSkill02d agononeA85Claude Code, Codex
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local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79kyesterdayMITA200Claude Code, Codex
playwright-climicrosoft/playwrightSkill100kyesterdayApache-2.0A19Claude Code
browser-automationopenclaw/openclawSkill394ktodayMITA36Claude Code
systematic-debuggingobra/superpowersSkill314k4d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143kyesterdayMITA95Claude Code