Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add LovelaceLoom/grok-plugin-cc/plugin install grokWrote 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/lovelaceloom/grok-plugin-cc/grok-research)<a href="https://agentmods.dev/skills/lovelaceloom/grok-plugin-cc/grok-research"><img src="https://agentmods.dev/badge/skills/lovelaceloom/grok-plugin-cc/grok-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/lovelaceloom/grok-plugin-cc/grok-research"><img src="https://agentmods.dev/badge/skills/lovelaceloom/grok-plugin-cc/grok-research.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00063 | $0.00707 |
| Opus 5 | $0.00032 | $0.00353 |
| Sonnet 5 | $0.00013 | $0.00141 |
| Haiku 4.5 | $0.00006 | $0.00071 |
Grade A, and why
grok-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 10d 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grok — Deep Research
Use this skill for non-trivial investigation tasks that benefit from Grok's full reasoning + verification stack. The companion sets sane research defaults:
--effort max— requested by default, but only applied on models that support reasoning effort. The current default model (grok-build) declares none, so the companion strips--effortwith a stderr warning. The real depth here comes from web search +--check, not--effort.- Web search enabled by default — Grok queries the live web during reasoning.
- Web fetch (
web_fetch) enabled by default (v1.2.0) — Grok can fetch a specific URL the user pasted, not just search. Opt out with--no-web-fetch. --checkenabled by default — Grok appends a self-verification loop and revises its own answer.
Override any of these with the flags below if the user explicitly asks for a cheaper / faster / web-less run.
When to use
- The user asks "research…", "investigate…", "find out…", "what's the current state of…", "is X still true as of ".
- Claims need verification against live sources.
- The task is research-shaped, not code-shaped (for coding tasks →
grok-rescue).
Do not use this skill for:
- One-off questions or quick lookups →
grok-ask. - Long-form coding / fixing / refactoring →
grok-rescue. - Image generation →
grok-imagine.
How to invoke
Run exactly one bash command:
node "${CLAUDE_PLUGIN_ROOT}/scripts/companion.mjs" research "<the user's research question, properly quoted>"
CLAUDE_PLUGIN_ROOT is set by both Claude Code and Codex CLI.
Common flags
--model <name>— override default Grok model.--effort <low|medium|high|xhigh|max>— override the defaultmax. Usehighor lower for cheaper runs.--no-check— disable the self-verification loop (faster, less rigorous).--no-web-search— disable live web search (rare; usually leave on).--no-web-fetch— disable the default-on web_fetch tool (rare).--stream— stream the answer live as Grok produces it (good for long runs).--timeout <duration>—0for unbounded (default).5m,30m, etc.
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.
- 10d ago First seen · 53 lines · 63 tokens per session scan A 62c470d60c96
grok-research is a skill published in the GitHub repository LovelaceLoom/grok-plugin-cc (5 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 63 tokens to every session and 707 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
ucai-patterns
Use when the user asks about Claude Code best practices, how to write agents, how to use hooks, how to manage context, or how to work effectively with Claude Code's native systems.
architect
This skill should be used when the user asks to "design system architecture", "evaluate microservices vs monolith", "create architecture diagrams", "analyze dependencies", "choose a database", "plan for scalability", "make technical decisions", or "review system design".
backend
This skill should be used when the user asks to "design REST APIs", "optimize database queries", "implement authentication", "build microservices", "review backend code", "set up GraphQL", "handle database migrations", or "load test APIs".
frontend-design
Use when user asks to build a web component, page, or application, or when the task involves frontend design, HTML/CSS generation, or UI layout. Applies specific rules for typography, OKLCH color, layout, motion, interaction, and UX writing to produce distinctive, production-grade interfaces that avoid generic AI…
lineage
Use when user invokes /lineage with a column name (optionally qualified with table/schema). Also triggers on "trace this column", "where does X come from", "what reads from Y table". Traces column-level data lineage through SQL, Kafka, Spark, JDBC, and ORM codebases. Produces a structured lineage path with confidence…
explain
Use when user invokes /explain with a file path, directory path, function/class name, or natural language concept. Also triggers on "explain this", "how does X work", "walk me through". Produces a structured, layered explanation of what the code does, how it connects, and where to start if you need to change it. Do…