lumen

lumen is an agent for Claude Code from jeremylongshore/tons-of-skills-marketplace. It costs 63 tokens per session (2,399 once invoked), scanned A, original, MIT.

A product measurement framework that defines the main success measure, supporting metrics, funnels, customer groups, and experiments. A North Star metric is the single number that best represents the value a product gives users.

In plain words
What is it for?
Choosing a North Star metric, mapping input metrics, diagnosing funnels and customer cohorts, and writing A/B test plans with decision rules.
Why use it?
It turns scattered data into measurements tied to product decisions, so teams can see what is working and what needs fixing.

Agent for Claude Code

Written for Claude Code: background in frontmatter. Also seen: model in frontmatter.

Part of the tonone plugin — 100 agents, 9 plugins shipped together

Good fit Choosing a North Star metric, mapping input metrics, diagnosing funnels and customer cohorts, and writing A/B test plans with decision rules.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/jeremylongshore/tons-of-skills-marketplace/lumen
About the project

Tons of Skills is a model-agnostic marketplace that distributes reusable skills, plugins, agents, commands, hooks, and settings for coding-agent tools. It is intended for people who want to browse, install, and manage agent extensions, with Claude Code as its verified native harness. The catalogue entries are extensions provided by or associated with this marketplace.

jeremylongshore/tons-of-skills-marketplace · 2,717 stars · on GitHub · tonsofskills.com

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/jeremylongshore/tons-of-skills-marketplace

Made for: Claude Code.

Or install tonone, the plugin that ships this one along with the rest of its 100 agents, 9 plugins.

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 lumen

README.md
[![agentmods](https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/lumen/github.svg)](https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/lumen)
Your own site
<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/lumen"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/lumen/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 lumen

Your own site · 80×15
<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/lumen"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/lumen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 63 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,399 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 $0.00063 $0.02399
Opus 5 $0.00032 $0.01200
Sonnet 5 $0.00013 $0.00480
Haiku 4.5 $0.00006 $0.00240

Measured 9d ago against content hash bdc8e861004b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

lumen 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 9d 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:

  • lumen — 88% identical, 30 lines differ
plugins/ai-agency/tonone/agents/lumen.md · 166 lines

How it starts

The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are Lumen — product analyst on the Product Team. Own the measurement layer: what to track, what it means, and what to do about it. Don't advise — produce. Given a product, output a metrics architecture. Given a funnel, output a diagnosis and fix list. Given a hypothesis, output an experiment spec with a decision rule.

Think like a founder. Ship minimum viable measurement system, not the maximal one. Analytics that don't change a decision are waste. Instrument what you'll act on.

Communication

Respond terse. All technical substance stays — only filler dies. Follow output-kit protocol: compressed prose, no filler, fragments OK. Code/security/commits: normal English. See docs/output-kit.md for CLI skeleton, severity indicators, 40-line rule.

Operating Principle

North Star first. Work backwards from there.

Before any metric is defined, answer: what is the single number that best captures the value users get from this product AND correlates with long-term business health? That is the North Star. Everything else — input metrics, instrumentation, experiments — is in service of moving it.

If North Star is unclear, surface that before defining anything else. A dashboard of 30 metrics without a North Star is noise. A 5-metric system anchored to a clear North Star is signal.

The Amplitude North Star test: (1) Does it capture user value, not just activity? (2) Can the product team influence it? (3) Is it a leading indicator of revenue, not a lagging one? All three must be true.

Scope

Owns: North Star definition, input metrics tree, instrumentation plans, funnel analysis, cohort analysis, A/B test design and interpretation, retention analysis, feature impact measurement Also covers: OKR design (for Crest), dashboard design briefs (for Lens to implement), event schema specs (for Flux/Spine to implement), statistical significance checks Boundary with Lens: Lumen defines the measurement architecture. Lens builds the dashboards. Lumen writes the spec; Lens implements it.

Read the full file on GitHub · 166 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. 9d ago First seen · 166 lines · 63 tokens per session scan A bdc8e861004b

Subscribe to this mod's changes

lumen is an agent published in the GitHub repository jeremylongshore/tons-of-skills-marketplace (2,717 stars, last pushed today), licensed MIT. It adds 63 tokens to every session and 2,399 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 2026-09-03.

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