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/exa-searchnpx skills add mturac/everything-openai-codex --skill exa-searchgit clone --depth 1 https://github.com/mturac/everything-openai-codexWrote 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/mturac/everything-openai-codex/exa-search)<a href="https://agentmods.dev/skills/mturac/everything-openai-codex/exa-search"><img src="https://agentmods.dev/badge/skills/mturac/everything-openai-codex/exa-search.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00049 | $0.01238 |
| Opus 5 | $0.00024 | $0.00619 |
| Sonnet 5 | $0.00010 | $0.00248 |
| Haiku 4.5 | $0.00005 | $0.00124 |
Grade A, and why
exa-search 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 6d 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.
This is a copy
98% identical to exa-search — 6 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 — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Exa Search
Neural search for web content, code, companies, and people via the Exa MCP server.
When to Activate
- User needs current web information or news
- Searching for code examples, API docs, or technical references
- Researching companies, competitors, or market players
- Finding professional profiles or people in a domain
- Running background research for any development task
- User says "search for", "look up", "find", or "what's the latest on"
MCP Requirement
Exa MCP server must be configured. Add to ~/.codex.json:
"exa-web-search": {
"command": "npx",
"args": ["-y", "exa-mcp-server"],
"env": { "EXA_API_KEY": "YOUR_EXA_API_KEY_HERE" }
}
Get an API key at exa.ai.
Core Tools
web_search_exa
General web search for current information, news, or facts.
web_search_exa(query: "latest AI developments 2026", numResults: 5)
Parameters:
| Param | Type | Default | Notes |
|---|---|---|---|
query |
string | required | Search query |
numResults |
number | 8 | Number of results |
web_search_advanced_exa
Filtered search with domain and date constraints.
web_search_advanced_exa(
query: "React Server Components best practices",
numResults: 5,
includeDomains: ["github.com", "react.dev"],
startPublishedDate: "2025-01-01"
)
Parameters:
| Param | Type | Default | Notes |
|---|---|---|---|
query |
string | required | Search query |
numResults |
number | 8 | Number of results |
includeDomains |
string[] | none | Limit to specific domains |
excludeDomains |
string[] | none | Exclude specific domains |
startPublishedDate |
string | none | ISO date filter (start) |
endPublishedDate |
string | none | ISO date filter (end) |
get_code_context_exa
Find code examples and documentation from GitHub, Stack Overflow, and docs sites.
get_code_context_exa(query: "Python asyncio patterns", tokensNum: 3000)
Parameters:
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.
- 6d ago First seen · 170 lines · 49 tokens per session scan A 5a354807f448
exa-search is a skill published in the GitHub repository mturac/everything-openai-codex (89 stars, last pushed 12d ago), licensed MIT. It adds 49 tokens to every session and 1,238 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to exa-search, differing in 6 lines, and is treated as a copy.
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validate-harness
Release-readiness umbrella check for a scaffolded harness — runs doctor, witness verify, hardcoded-path scan, MCP server config, and GCP Secret Manager validation in one shot. Exits non-zero if any sub-check fails.
merge-prep
Pre-merge analysis and preparation. Analyzes source branch vs target branch: commit stats, conflict detection, file impact. Analysis-only v1 — outputs report + suggested commands, does not auto-merge. Use when: user says 'merge prep', 'pre-merge', 'merge analysis', or /merge-prep.
simplify
Wrap-up refactoring — simplify code, eliminate duplication, preserve behavior.
autonomous-loops
Patterns and architectures for autonomous loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems. Use when setting up autonomous development workflows, choosing the right loop architecture, or building CI/CD-style continuous development pipelines.
quality-gate
Production quality gate for agent sessions. Activates on session stop to evaluate work quality using 4-dimension weighted scoring (completeness, honesty, deferral ratio, work evidence). Catches rationalization patterns, verifies test claims, and generates handoff artifacts for session continuity. Use sprint contracts…
yao-process
Yao process execution expert. ALWAYS invoke this skill when the user needs to call a Yao process, query data models, run scripts, or check process permissions. Do not call processes without checking this skill first.