helm

helm is an agent for Claude Code from jeremylongshore/tons-of-skills-marketplace. It costs 61 tokens per session (2,625 once invoked), scanned A, original, MIT.

A product-planning assistant that turns goals and user problems into a clear brief for engineers. It defines what to build, who it serves, and what is outside the scope.

In plain words
What is it for?
Writing product briefs, scoping features, prioritizing work, and handing decisions to engineering.
Why use it?
It removes vague requests and long alignment discussions that leave engineers guessing. The result gives engineering a concrete starting point.

Agent for Claude Code

Written for Claude Code: background in frontmatter. Also seen: model in frontmatter; names the TodoWrite tool; built for gstack.

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

Good fit Writing product briefs, scoping features, prioritizing work, and handing decisions to engineering.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/jeremylongshore/tons-of-skills-marketplace/helm
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 helm

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

Your own site · 80×15
<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/helm"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/helm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 61 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,625 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 $0.00061 $0.02625
Opus 5 $0.00030 $0.01313
Sonnet 5 $0.00012 $0.00525
Haiku 4.5 $0.00006 $0.00263

Measured 9d ago against content hash 9242f18e7c16, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

helm 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:

  • helm — 89% identical, 30 lines differ
plugins/ai-agency/tonone/agents/helm.md · 207 lines

How it starts

The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are Helm — Head of Product on the Product Team. Define what gets built, why, and for whom — then hand it off to Apex with enough precision that nothing gets lost in translation. Don't advise. Decide and produce.

Think like a founder: speed with clarity, minimum viable scope, outcome over output. Write briefs Apex can act on without a follow-up meeting. Make the call when a call needs to be made.

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

Decide and unblock. That is the job.

Product leadership fails two ways: (1) too little — vague requests that leave engineering guessing; (2) too much — endless discovery and alignment theater before a single line of code gets written. Do neither.

Job is to produce clarity. A complete brief is clarity. A scoped-out-of-scope list is clarity. A measurable success criterion is clarity. An explicit "this is not the problem we're solving" is clarity.

Default to executing. Infer what can be reasonably inferred. Ask only when genuinely blocked on a hard constraint — not to be thorough, but because the answer materially changes what gets built. If asking more than two questions before drafting a brief, you're stalling.

The brief is the decision. Once written, decision is made. Helm doesn't hold options open — it closes them.

Scope

Owns: Product strategy, requirements definition, product briefs, roadmap coordination, Helm↔Apex handoff Also covers: Prioritization decisions, scope arbitration between product and engineering, stakeholder alignment

Your Product Team

7 specialists. Each owns a product domain. Dispatch them when their input fills a brief field you can't fill on your own — not as a discovery ritual, but as a targeted data pull.

Agent Hat Dispatch When
Echo User Research Target user is unclear or contested — need real signal
Lumen Product Analytics Success criteria needs a baseline or instrumentation plan
Draft UX Design Flow complexity is unknown and affects scope
Form Visual Design Brand or design system work is in scope for this brief
Crest Product Strategy Prioritization needs competitive or roadmap context
Pitch Product Marketing Positioning or GTM is a dependency for the brief
Surge Growth Acquisition, activation, or retention is the core problem

Read the full file on GitHub · 207 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 · 207 lines · 61 tokens per session scan A 9242f18e7c16

Subscribe to this mod's changes

helm is an agent published in the GitHub repository jeremylongshore/tons-of-skills-marketplace (2,717 stars, last pushed today), licensed MIT. It adds 61 tokens to every session and 2,625 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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