enterprise-search

enterprise-search is a skill for Cursor from ZhixiangLuo/10xProductivity. It costs 136 tokens per session (491 once invoked), scanned A, original, MIT.

A workflow for searching connected company knowledge sources, such as Slack messages, Confluence documentation, Jira issues, Linear tasks, Notion pages, and GitHub repositories, from one question.

In plain words
What is it for?
Use it to find past discussions, bug tickets, technical decisions, runbooks, and the people or projects associated with them.
Why use it?
It reduces the need to search each service separately when information is spread across company chats, documents, code, and issue trackers. It checks which sources are connected and combines relevant results.

Skill for Cursor

Written for Cursor: installed under .cursor/.

Good fit Use it to find past discussions, bug tickets, technical decisions, runbooks, and the people or projects associated with them.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/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.

Any agent
npx skills add ZhixiangLuo/10xProductivity --skill enterprise-search
Clone the repo
git clone --depth 1 https://github.com/ZhixiangLuo/10xProductivity

Made for: Cursor.

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/skills/zhixiangluo/10xproductivity/enterprise-search/github.svg)](https://agentmods.dev/skills/zhixiangluo/10xproductivity/enterprise-search)
Your own site
<a href="https://agentmods.dev/skills/zhixiangluo/10xproductivity/enterprise-search"><img src="https://agentmods.dev/badge/skills/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/skills/zhixiangluo/10xproductivity/enterprise-search"><img src="https://agentmods.dev/badge/skills/zhixiangluo/10xproductivity/enterprise-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 136 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 491 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00136 $0.00491
Opus 5 $0.00068 $0.00246
Sonnet 5 $0.00027 $0.00098
Haiku 4.5 $0.00014 $0.00049

Measured 11d ago against content hash f45633f1a2b1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, 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.

.cursor/skills/enterprise-search/SKILL.md · 44 lines

What it actually says

One question. Every connected tool. One synthesized answer.

Search your company's knowledge across Slack, Confluence, Jira, Linear, Notion, GitHub, and more — simultaneously, in a single query.


Before you search: check connection status

ls verified_connections.md 2>/dev/null && grep -c "^##" verified_connections.md || echo "0"
  • 1+ tools connected → read verified_connections.md (capability index), then follow workflows/enterprise-search/enterprise-search.md for the search. That workflow always uses Slack + Confluence when connected, may include AI-synthesized search tools listed only in verified_connections.md (per each connection file), and adds Jira/Linear/Notion/GitHub when relevant.
  • Not connected / empty → read setup.md. Your agent handles the full connection flow — credentials, SSO, verification — in one session. ~5 minutes per tool.

What you can ask

  • "Search for the discussion about the database migration"
  • "Find any Jira tickets related to the login timeout bug"
  • "What was the decision about the API versioning approach?"
  • "Is there a Confluence runbook for on-call handoffs?"
  • "Who worked on the payments refactor and what did they decide?"

The search workflow handles routing, parallel execution across tools, and synthesized results. You don't need to specify which tool — the agent figures that out.

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 · 44 lines · 136 tokens per session scan A f45633f1a2b1

Subscribe to this mod's changes

enterprise-search is a skill published in the GitHub repository ZhixiangLuo/10xProductivity (474 stars, last pushed 2mo ago), licensed MIT. It adds 136 tokens to every session and 491 once invoked, about $0.0007 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 2026-08-30.

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