gingiris-launch

A product-launch playbook covering Product Hunt, a website where new products are presented and voted on by a community. It lays out activities before launch, on launch day, and during the following week.

In plain words
What is it for?
Use it to choose hunters, prepare maker comments, schedule launch-day activity, coordinate multiple channels, and maintain attention after release.
Why use it?
It gives launch teams a sequence for timing, outreach, comments, and follow-up, including guidance intended to avoid reduced platform visibility.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/gingiris-1031/competitor-analysis-tool/gingiris-launch
Any agent
npx skills add Gingiris-1031/Competitor-analysis-tool --skill gingiris-launch
Clone the repo
git clone --depth 1 https://github.com/Gingiris-1031/Competitor-analysis-tool

Made for: Claude Code, Codex.

Per session 407 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,086 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00407 $0.02086
Opus 5 $0.00204 $0.01043
Sonnet 5 $0.00081 $0.00417
Haiku 4.5 $0.00041 $0.00209

Measured 3d ago against content hash ce52a5032643, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gingiris-launch 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 3d 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.

gingiris-skills/gingiris-launch/SKILL.md · 124 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. 3d ago First seen · 124 lines · 407 tokens per session scan A ce52a5032643

Subscribe to this mod's changes

gingiris-launch is a skill published in the GitHub repository Gingiris-1031/Competitor-analysis-tool (108 stars, last pushed 4d ago), with no licence file. It adds 407 tokens to every session and 2,086 once invoked, about $0.0020 per session on Opus 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 2026-08-30.

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