using-glean

A guide for using Glean, a company search and knowledge system, through its MCP tools. It covers finding internal documents, people, meetings, email, code, decisions, and work activity.

In plain words
What is it for?
Use it to answer questions from internal wikis, policies, design documents, meeting records, calendars, email, company code, or employee information.
Why use it?
It helps the agent choose the right company-data search for a question and explains what to do when the Glean connection is unavailable.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/gleanwork/claude-plugins/using-glean
Any agent
npx skills add gleanwork/claude-plugins --skill using-glean
Clone the repo
git clone --depth 1 https://github.com/gleanwork/claude-plugins

Made for: Claude Code, Codex.

Per session 171 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,148 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00171 $0.01148
Opus 5 $0.00086 $0.00574
Sonnet 5 $0.00034 $0.00230
Haiku 4.5 $0.00017 $0.00115

Measured 2d ago against content hash 52fc10fd21d6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

using-glean 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 2d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

plugins/glean/skills/using-glean/SKILL.md · 55 lines

How it starts

The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Using Glean

The Glean MCP server exposes a family of tools that let the assistant query the user's company knowledge: documents, people, meetings, email, internal code, the user's activity feed, structured memory, and the knowledge graph. This skill is the entry point. It maps a user's question to the right tool, names the rules that apply across all of them, and links to per-tool reference files that carry the deep syntax.

Where these tools live

The tools listed below come from the user's Glean MCP server connection. Refer to them by their bare names (search, employee_search, meeting_lookup, …) — the assistant resolves them against the active tool inventory.

In the raw MCP tool list, Glean tools appear as mcp__glean_[server-name]__[tool] where [server-name] is the user's configured server identifier (e.g., default, production, acme). The tool suffix after the final __ is always consistent across deployments. Use whatever Glean server is visible in your tool inventory.

If no Glean tools are visible, ask the user to set up Glean by prompting the harness (for example, Set up Glean for me).

Intent → tool decision tree

The user is asking about... Reach for Reference
Documents, wikis, policies, RFCs, specs search search.md
A complex question that needs synthesis across sources chat chat.md
Internal source code, files, commits across repos code_search code-search.md
People, teams, org structure, reporting lines employee_search employee-search.md
Meetings, transcripts, decisions, action items meeting_lookup meeting-lookup.md
Gmail messages, threads, attachments gmail_search gmail-search.md
Outlook messages, threads, attachments outlook_search outlook-search.md
Reading a specific URL / document read_document read-document.md
The user's own recent activity (standup, weekly summary) user_activity user-activity.md
The user's stored memories / personalization memory (+ memory_schema) memory.md
Structured entity / relationship queries knowledge_graph_query (+ knowledge_graph_schema) knowledge-graph.md

Read the full file on GitHub · 55 lines

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. 2d ago First seen · 55 lines · 171 tokens per session scan A 52fc10fd21d6

Subscribe to this mod's changes

using-glean is a skill published in the GitHub repository gleanwork/claude-plugins (25 stars, last pushed 12d ago), licensed MIT. It adds 171 tokens to every session and 1,148 once invoked, about $0.0009 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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