enterprise-search

enterprise-search is a command for Claude Code from ZhixiangLuo/10xProductivity. It costs 0 tokens per session (340 once invoked), scanned A, original, MIT.

A command that searches connected workplace tools, such as Slack, Confluence, Jira, Linear, Notion, and GitHub, in one query.

In plain words
What is it for?
Use it to find internal answers, incident discussions, procedures, project issues, feature requests, and related code.
Why use it?
It removes the need to search each company system separately when looking for decisions, documents, tickets, or code.

Command for Claude Code

Written for Claude Code: $ARGUMENTS substitution.

Good fit Use it to find internal answers, incident discussions, procedures, project issues, feature requests, and related code.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/zhixiangluo/10xproductivity/enterprise-search
Install

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.

Clone the repo
git clone --depth 1 https://github.com/ZhixiangLuo/10xProductivity

Made for: Claude Code.

Wrote 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.

agentmods badge for enterprise-search

README.md
[![agentmods](https://agentmods.dev/badge/commands/zhixiangluo/10xproductivity/enterprise-search/github.svg)](https://agentmods.dev/commands/zhixiangluo/10xproductivity/enterprise-search)
Your own site
<a href="https://agentmods.dev/commands/zhixiangluo/10xproductivity/enterprise-search"><img src="https://agentmods.dev/badge/commands/zhixiangluo/10xproductivity/enterprise-search/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.

agentmods 80×15 button for enterprise-search

Your own site · 80×15
<a href="https://agentmods.dev/commands/zhixiangluo/10xproductivity/enterprise-search"><img src="https://agentmods.dev/badge/commands/zhixiangluo/10xproductivity/enterprise-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 340 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.00340
Opus 5 $0.00000 $0.00170
Sonnet 5 $0.00000 $0.00068
Haiku 4.5 $0.00000 $0.00034

Measured 11d ago against content hash 936cfd28145c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

enterprise-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 11d 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.

.claude/commands/enterprise-search.md · 34 lines

What it actually says

Search institutional knowledge across every connected tool simultaneously.

One query → Slack + Confluence (always when connected) + any AI-synthesized search tools in verified_connections.md + Jira/Linear/Notion/GitHub when relevant → synthesized answer.

Steps

  1. Check connection status:

    ls verified_connections.md 2>/dev/null && grep -c "^##" verified_connections.md || echo "0"
    
  2. If 1+ tools connected: Read verified_connections.md (your active tool index), then follow workflows/enterprise-search/enterprise-search.md to search for: $ARGUMENTS

  3. If not connected / empty: Read setup.md. It walks through connecting each tool you use — credentials, SSO, verification — your agent runs the whole flow. ~5 min per tool. Once set up, run this command again.

What this searches

Tool What it finds
Slack Decisions, incident threads, "why did we do X"
Confluence Runbooks, architecture docs, procedures
Jira Tickets, bugs, epics, sprint history
Linear Project issues and feature requests
Notion Pages and databases
GitHub Code, PRs, issues (code-related queries only)
Other If verified_connections.md lists an AI assistant or multi-source knowledge search, follow that connection file in parallel — see the workflow.

Only connected tools are searched. The workflow adapts to whatever is in verified_connections.md.

Changes

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.

  1. 11d ago First seen · 34 lines · 0 tokens per session scan A 936cfd28145c

Subscribe to this mod's changes

enterprise-search is a command published in the GitHub repository ZhixiangLuo/10xProductivity (474 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 340 tokens. 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 2026-08-30.