claude-codex-settings is a collection of configurations and reusable extensions for Claude Code, OpenAI Codex, Cursor, and related coding tools. Developers use its skills, commands, hooks, agents, plugins, and MCP servers to shape coding-agent workflows and connect alternative model APIs. The catalogue entries are components of this collection that can be installed into supported coding tools.
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 fcakyon/claude-codex-settings --skill mongodb-query-optimizergit clone --depth 1 https://github.com/fcakyon/claude-codex-settingsWrote 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/fcakyon/claude-codex-settings/mongodb-query-optimizer)<a href="https://agentmods.dev/skills/fcakyon/claude-codex-settings/mongodb-query-optimizer"><img src="https://agentmods.dev/badge/skills/fcakyon/claude-codex-settings/mongodb-query-optimizer/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/fcakyon/claude-codex-settings/mongodb-query-optimizer"><img src="https://agentmods.dev/badge/skills/fcakyon/claude-codex-settings/mongodb-query-optimizer.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 | $0.00098 | $0.02390 |
| Opus 5.5 | $0.00039 | $0.00956 |
| Sonnet 5.5 | $0.00020 | $0.00478 |
| Haiku 4.5 | $0.00010 | $0.00239 |
Grade A, and why
mongodb-query-optimizer 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- mongodb-query-optimizer — 100% identical, 40 lines differ
- mongodb-query-optimizer — 100% identical, 0 lines differ
- mongodb-query-optimizer — 88% identical, 63 lines differ
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MongoDB Query Optimizer
When this skill is invoked
Invoke only when the user wants:
- Query/index optimization or performance help
- Why a query is slow or how to speed it up
- Slow queries on their cluster and/or how to optimize them
Do not invoke for routine query authoring unless the user has requested help with optimization, slow queries, or indexing.
High Level Workflow
General Performance Help
If the user wants to examine slow queries, or is looking for general performance suggestions (not regarding any particular query):
- Use MongoDB MCP server atlas-get-performance-advisor tool to fetch slow query logs and performance advisor output
- Make suggestions based on this information
If Atlas MCP Server for Atlas is not configured or you don’t have enough information to run atlas-get-performance-advisor against the correct cluster, tell the user that general performance analysis requires Atlas MCP Server configuration with API credentials, and suggest they configure it or ask about a specific query instead.
Help with a Specific Query
If the user is asking about a particular query:
- Use collection-indexes, explain, and find MCP tools to get existing indexes on the collection, explain() output for the query, and a sample document from the collection
- Use atlas-get-performance-advisor MCP tool to fetch slow query logs and performance advisor output
Then make an optimization suggestion based on collected information and MongoDB best practices and examples from reference files. Prefer creating an index that fully covers the query if possible. If you cannot use MongoDB MCP Server then still try to make a suggestion.
MCP: available tools
How to invoke. Call the MongoDB MCP server with the exact tool name as toolName and a single arguments object as arguments. Do not pass the tool name as an option, query param, or nested key; pass it as the MCP tool name and the parameters as the arguments object. Full MCP Server tool reference: MongoDB MCP Server Tools.
What ships with it
4 files 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.
- 1mo ago First seen · 150 lines · 98 tokens per session scan A 62a5bff5f405
mongodb-query-optimizer is a skill published in the GitHub repository fcakyon/claude-codex-settings (1,181 stars, last pushed today), licensed Apache-2.0. It adds 98 tokens to every session and 2,390 once invoked, about $0.0004 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 2026-09-03.
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