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 agentmods add skills/mturac/everything-openai-codex/deep-researchnpx skills add mturac/everything-openai-codex --skill deep-researchgit clone --depth 1 https://github.com/mturac/everything-openai-codexWhat 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 | $0.00048 | $0.01144 |
| Opus 5 | $0.00024 | $0.00572 |
| Sonnet 5 | $0.00010 | $0.00229 |
| Haiku 4.5 | $0.00005 | $0.00114 |
Grade B, and why
deep-research scanned grade B with 1 finding 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 yesterday.
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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
Both together give the best coverage. Configure in `~/.codex.json` or `~/.codex/config.toml`. This is a copy
95% identical to deep-research — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Research
Produce thorough, cited research reports from multiple web sources using firecrawl and exa MCP tools.
When to Activate
- User asks to research any topic in depth
- Competitive analysis, technology evaluation, or market sizing
- Due diligence on companies, investors, or technologies
- Any question requiring synthesis from multiple sources
- User says "research", "deep dive", "investigate", or "what's the current state of"
MCP Requirements
At least one of:
- firecrawl —
firecrawl_search,firecrawl_scrape,firecrawl_crawl - exa —
web_search_exa,web_search_advanced_exa,crawling_exa
Both together give the best coverage. Configure in ~/.codex.json or ~/.codex/config.toml.
Workflow
Step 1: Understand the Goal
Ask 1-2 quick clarifying questions:
- "What's your goal — learning, making a decision, or writing something?"
- "Any specific angle or depth you want?"
If the user says "just research it" — skip ahead with reasonable defaults.
Step 2: Plan the Research
Break the topic into 3-5 research sub-questions. Example:
- Topic: "Impact of AI on healthcare"
- What are the main AI applications in healthcare today?
- What clinical outcomes have been measured?
- What are the regulatory challenges?
- What companies are leading this space?
- What's the market size and growth trajectory?
Step 3: Execute Multi-Source Search
For EACH sub-question, search using available MCP tools:
With firecrawl:
firecrawl_search(query: "<sub-question keywords>", limit: 8)
With exa:
web_search_exa(query: "<sub-question keywords>", numResults: 8)
web_search_advanced_exa(query: "<keywords>", numResults: 5, startPublishedDate: "2025-01-01")
Search strategy:
- Use 2-3 different keyword variations per sub-question
- Mix general and news-focused queries
- Aim for 15-30 unique sources total
- Prioritize: academic, official, reputable news > blogs > forums
Step 4: Deep-Read Key Sources
For the most promising URLs, fetch full content:
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.
- yesterday First seen · 155 lines · 48 tokens per session scan B 2c1a19cd9c32
deep-research is a skill published in the GitHub repository mturac/everything-openai-codex (89 stars, last pushed 7d ago), licensed MIT. It adds 48 tokens to every session and 1,144 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). It is 95% identical to deep-research, differing in 4 lines, and is treated as a copy.
Other skills, from other repositories
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oma-scholar
Scholarly research companion using Knows sidecar spec (.knows.yaml). Generates, validates, reviews, queries, and compares structured research-paper sidecars, and fetches them from knows.academy. Use for academic literature search, survey synthesis, paper authoring assistance, and peer review with token-efficient…
oma-hwp
Convert HWP / HWPX / HWPML files to Markdown using kordoc. Extracts text, headings, tables, lists, images, footnotes, and hyperlinks. Use for Korean word processor files (Hangul), government documents, and AI-ready data preparation.
browser_cdp
通过 Chrome DevTools Protocol (CDP) 连接已运行的浏览器，或扫描本机 CDP 端口，用于远程调试与多工具共享浏览器实例。.
compare-harnesses
Diff two scaffolded harnesses (ADR-031). Reports manifest meta drift + host list + per-file fingerprint changes (added/removed/changed). Exits 0 IDENTICAL, 1 DRIFT, 2 missing manifest. Use --bundle for the ADR-031 schema-1 JSON envelope.
skills-audit
Audit .agents/skills SKILL.md files. Use for recurring checks of duplicate, overlapping, stale, inconsistent, or broken skills and merge/delete candidates.