glean_run

A routing skill for discovering and running Glean skills for company tools such as Jira, Slack, Google Workspace, and Salesforce. Glean is an enterprise search and work assistant platform.

In plain words
What is it for?
Use it for enterprise-app tasks that need a Glean skill, including finding information or carrying out actions across supported company systems.
Why use it?
It provides a way to find the right company-tool workflow when no directly available tool matches the request. It also explains how to handle required sign-in setup.

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/cursor-plugins/glean_run
Any agent
npx skills add gleanwork/cursor-plugins --skill glean_run
Clone the repo
git clone --depth 1 https://github.com/gleanwork/cursor-plugins

Made for: Claude Code, Codex.

Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,010 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00014 $0.01010
Opus 5 $0.00007 $0.00505
Sonnet 5 $0.00003 $0.00202
Haiku 4.5 $0.00001 $0.00101

Measured yesterday against content hash fc6a3562f8e1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

glean_run 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 yesterday.

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

This is a copy

100% identical to glean_run — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

glean/skills/glean_run/SKILL.md · 125 lines

How it starts

The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Glean Run

Discover and use Glean skills to help with enterprise app tasks (Jira, Slack, Google Workspace, Salesforce, etc.) or actions you don't already have a tool for. Where possible, aim to complete the user's request end-to-end rather than just listing available skills.

Authentication

Authentication is handled exclusively by the setup tool. If any other tool returns a response containing [SETUP_REQUIRED], the user needs to (re-)authenticate via setup.

When this happens:

  1. Call setup (no arguments).
    • If no Server URL is configured, setup returns [SETUP_REQUIRED] with instructions. Relay them, ask the user for their work email, then call setup again with email set to what they provided.
    • Once a Server URL is configured, setup opens the Glean sign-in page in the browser and waits for sign-in.
  2. Once setup returns "Glean setup is complete", retry the original tool call.

Do not treat [SETUP_REQUIRED] as an error or try to work around it any other way.

Step 0: Verify Setup

Call setup (with no arguments). If the connection isn't ready, setup returns instructions — follow them and call setup again; it guides the whole flow. Once it returns "Glean setup is complete", proceed to Step 1.

Step 1: Plan tool usage

A small set of popular tools is directly available, and no discovery is needed to use them. Discover is complementary and recommended if the direct tools cannot satisfy the user request end to end.

Calling find_skills_and_tools

If no arguments were provided and the task can't be inferred from conversation context, ask the user what they'd like to do before proceeding.

Call find_skills_and_tools with the task descriptions.

Break the request into small, task-atomic queries — keep only the core action, dropping the surrounding context (recipients, timing, reasons, constraints) — and pass each as a separate entry in queries.

find_skills_and_tools({
  queries: [
    "<atomic sub-task 1>",
    "<atomic sub-task 2>"
  ]
})

Read the full file on GitHub · 125 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. yesterday First seen · 125 lines · 14 tokens per session scan A fc6a3562f8e1

Subscribe to this mod's changes

glean_run is a skill published in the GitHub repository gleanwork/cursor-plugins (3 stars, last pushed 12d ago), licensed MIT. It adds 14 tokens to every session and 1,010 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to glean_run, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens