multi-surface-strategy

multi-surface-strategy is a skill for Claude Code, Codex from DojoGenesis/mcp. It costs 95 tokens per session (2,766 once invoked), scanned A, original, MIT.

A product-planning method for deciding what distinct role each part of a product should play across desktop, mobile, web, API, or command-line interfaces.

In plain words
What is it for?
Use it when planning a product across several interfaces, adding a new interface, or resolving a fragmented user experience.
Why use it?
It helps prevent multiple versions of a product from becoming repetitive or disconnected.

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/dojogenesis/mcp/multi-surface-strategy
Any agent
npx skills add DojoGenesis/mcp --skill multi-surface-strategy
Clone the repo
git clone --depth 1 https://github.com/DojoGenesis/mcp

Made for: Claude Code, Codex.

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 multi-surface-strategy

README.md
[![agentmods](https://agentmods.dev/badge/skills/dojogenesis/mcp/multi-surface-strategy.svg)](https://agentmods.dev/skills/dojogenesis/mcp/multi-surface-strategy)
Your own site
<a href="https://agentmods.dev/skills/dojogenesis/mcp/multi-surface-strategy"><img src="https://agentmods.dev/badge/skills/dojogenesis/mcp/multi-surface-strategy.svg" alt="Measured on agentmods" height="20"></a>
Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,766 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 $0.00095 $0.02766
Opus 5 $0.00048 $0.01383
Sonnet 5 $0.00019 $0.00553
Haiku 4.5 $0.00010 $0.00277

Measured 3d ago against content hash f3c9c8c09885, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

multi-surface-strategy 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 3d 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.

internal/skills/bundled/strategic-thinking/multi-surface-strategy/SKILL.md · 286 lines

How it starts

The opening of the file, as written. The whole thing — 286 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Multi-Surface Product Strategy Skill

Version: 1.0 Purpose: To guide the design of a coherent multi-surface product strategy where each surface (e.g., desktop, mobile, web, API) has a unique, complementary role.


I. The Philosophy: Complement, Don't Compete

In a multi-surface world, the biggest mistake is to build the same product on every device. A desktop app, a mobile app, and a web app should not be clones of each other. They should be complementary surfaces, each optimized for the unique context in which it will be used.

Three principles guide this skill:

  1. Surfaces are for contexts, not devices. Users don't think "I need the mobile version." They think "I need to capture this idea quickly while I'm walking." Frame each surface by its context of use, not by its device type.

  2. The handoff is the feature. The most magical part of a multi-surface strategy is the seamless handoff between surfaces. This is what makes the whole greater than the sum of its parts. Invest heavily in sync architecture and handoff UX.

  3. Asymmetry is a feature. Not every surface needs every feature. The best multi-surface strategies give each surface a reason to exist that the others can't replicate. Symmetrical strategies (same features everywhere) are wasteful and boring.


II. When to Use This Skill

  • When planning a new product that will exist on multiple surfaces
  • When adding a new surface (e.g., a mobile app) to an existing product
  • When a multi-surface product feels fragmented or confusing
  • During a strategic review of a product line
  • After using product-positioning to identify unique value propositions for each surface
  • When deciding the rollout order for multiple surfaces

When NOT to use:

  • When the product genuinely only needs one surface
  • When the question is about positioning (use product-positioning first)
  • When the surfaces are already well-defined and the question is about execution

III. The Workflow

Read the full file on GitHub · 286 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. 3d ago First seen · 286 lines · 95 tokens per session scan A f3c9c8c09885

Subscribe to this mod's changes

multi-surface-strategy is a skill published in the GitHub repository DojoGenesis/mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 95 tokens to every session and 2,766 once invoked, about $0.0005 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 2026-08-31.

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