Awesome Codex Plugins is a curated catalogue and marketplace of installable plugins, skills, and related resources for OpenAI Codex and ChatGPT. It helps people find, create, validate, and submit extensions for Codex workflows across its app, command-line interface, and IDE extensions. The catalogue add-ons are the plugins, skills, agents, and hooks listed or supported by this project.
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 hashgraph-online/awesome-codex-plugins --skill launchfast-product-researchgit clone --depth 1 https://github.com/hashgraph-online/awesome-codex-pluginsWrote 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/hashgraph-online/awesome-codex-plugins/launchfast-product-research)<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/launchfast-product-research"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/launchfast-product-research/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/hashgraph-online/awesome-codex-plugins/launchfast-product-research"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/launchfast-product-research.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 | $0.00064 | $0.00611 |
| Opus 5.5 | $0.00026 | $0.00244 |
| Sonnet 5.5 | $0.00013 | $0.00122 |
| Haiku 4.5 | $0.00006 | $0.00061 |
Grade A, and why
launchfast-product-research 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 1mo 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LaunchFast Product Research
Use this skill for a fast, opinionated market scan across up to 10 keywords.
Inputs
If missing, ask once for:
- keywords to research
- optional target price band
- optional competition tolerance
Workflow
1. Run research
- Run
research_productsfor each keyword. - Prefer parallel tool calls when researching more than one keyword.
- Use
focus="balanced"andproduct_limit=20unless the user asks otherwise.
2. Extract core metrics per keyword
From the response, compute:
- products analyzed
- grade distribution
- median monthly revenue
- top product revenue
- average or median price
- average or median reviews
- brand concentration
- dominant brand
3. Score the market
Use this score out of 100:
score =
(% of products graded B5 or better) * 30
+ (median revenue >= 8000 ? 30 : (median revenue / 8000) * 30)
+ (median reviews < 300 ? 20 : (300 / median reviews) * 20)
+ (median price between 18 and 60 ? 20 : 10)
Competition bands:
- Low: median reviews < 200
- Medium: median reviews 200-800
- High: median reviews > 800
Verdicts:
- GO: score >= 65
- INVESTIGATE: score 40-64
- PASS: score < 40
4. Present results
Always show:
- a ranked summary table for all keywords
- a short deep dive for the top 3
Use this table shape:
## Product Opportunity Scan
| Rank | Keyword | Score | Market Grade | Top Revenue | Avg Price | Competition | Verdict |
|------|---------|-------|--------------|-------------|-----------|-------------|---------|
For each top-3 keyword include:
- products analyzed
- grade distribution
- revenue range
- price range
- review range
- best product snapshot
- one-sentence key insight
- risk flags
- verdict with 1-2 sentence rationale
Notes
- If a keyword has missing or zero search volume, explicitly call that out.
- If the results look too narrow or too broad, suggest the better keyword variant inline.
- Do not force a follow-up question at the end; only recommend next actions when the result is borderline or strong enough to justify it.
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.
- 1mo ago First seen · 103 lines · 64 tokens per session scan A 5988b9dafae2
launchfast-product-research is a skill published in the GitHub repository hashgraph-online/awesome-codex-plugins (1,419 stars, last pushed yesterday), licensed Apache-2.0. It adds 64 tokens to every session and 611 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 2026-09-05.
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