deck-iteration-workflow

deck-iteration-workflow is a skill for Claude Code, Codex from lossless-group/lossless-agent-skills. It costs 77 tokens per session (2,004 once invoked), scanned A, original, MIT.

A staged workflow for building slide-only Astro websites for fundraising presentations. Astro is a web framework, and fundraising presentations are decks used to explain a company or investment opportunity to potential investors.

In plain words
What is it for?
Use it when creating or modifying slide decks, managing slide versions, or building an Astro presentation for a fundraising process.
Why use it?
It breaks deck development into manageable stages, from shaping the whole story to separating slides, cleaning up code, and adding interactive features.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Claude Code.

Good fit Use it when creating or modifying slide decks, managing slide versions, or building an Astro presentation for a fundraising process.

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Install with agentmods
npx agentmods add skills/lossless-group/lossless-agent-skills/deck-iteration-workflow
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.

Any agent
npx skills add lossless-group/lossless-agent-skills --skill deck-iteration-workflow
Clone the repo
git clone --depth 1 https://github.com/lossless-group/lossless-agent-skills

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 deck-iteration-workflow

README.md
[![agentmods](https://agentmods.dev/badge/skills/lossless-group/lossless-agent-skills/deck-iteration-workflow/github.svg)](https://agentmods.dev/skills/lossless-group/lossless-agent-skills/deck-iteration-workflow)
Your own site
<a href="https://agentmods.dev/skills/lossless-group/lossless-agent-skills/deck-iteration-workflow"><img src="https://agentmods.dev/badge/skills/lossless-group/lossless-agent-skills/deck-iteration-workflow/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 deck-iteration-workflow

Your own site · 80×15
<a href="https://agentmods.dev/skills/lossless-group/lossless-agent-skills/deck-iteration-workflow"><img src="https://agentmods.dev/badge/skills/lossless-group/lossless-agent-skills/deck-iteration-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,004 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 $0.00077 $0.02004
Opus 5 $0.00039 $0.01002
Sonnet 5 $0.00015 $0.00401
Haiku 4.5 $0.00008 $0.00200

Measured 10d ago against content hash 1b10ad97aff1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

deck-iteration-workflow 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 10d 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.

deck-iteration-workflow/SKILL.md · 198 lines

How it starts

The opening of the file, as written. The whole thing — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deck Iteration Workflow

A structured approach to developing slide decks for fundraise processes using the iterative methodology established in the calmstorm-decks project.

When to use this skill

  • Creating a new slides-only Astro site for fundraise processes
  • Managing slide variants and iterations during development
  • Implementing the phased workflow for slide deck development
  • Working with the calmstorm-decks project patterns
  • When the user mentions "deck iteration", "slide variants", or fundraise slide development workflows

Overview

flowchart LR
    A[Single-Page Narrative] --> B[Individual Slides]
    B --> C[Cleanup / Componentization]
    C --> D[Features]
    D --> E[Full Deck]
    E --> F[Advanced Interactivity]

This workflow provides a structured approach to developing slide decks for fundraise processes based on the patterns and workflows discovered in the calmstorm-decks project. It emphasizes starting from the whole narrative as a single-page Astro scroll deck, then splitting to individual slides, then cleaning up and componentizing — followed by feature enhancement, full-deck completion, and advanced interactivity.

Why holistic-first: coding agents (Claude Code and generative AI generally) produce better creative flow and more coherent design when they can reason about the entire deck at once. An earlier version of this workflow started with plain wireframe HTML on a per-slide basis; that produced fragmented design and slow iteration. Building the whole narrative as one Astro page where each slide is a section component lets the agent improvise around theme/layout boundaries with the full arc visible.

Core Principles

  1. Holistic before piecewise - Start with the whole narrative on one page so the agent can reason about it as a coherent arc; split to individual slides only after the through-line is right
  2. Start fresh - Break from established patterns that have proven arduous and time-consuming
  3. Iterative perfection - Get something playable and clean before adding complexity
  4. Variant generation - Create multiple variants to explore design options quickly
  5. Phase-based development - Follow the structured progression: single-page narrative → individual slides → cleanup/componentization → features → full deck → advanced interactivity
  6. Design system foundation - Build explicit design systems only after achieving aesthetic harmony

Read the full file on GitHub · 198 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 10d ago First seen · 198 lines · 77 tokens per session scan A 1b10ad97aff1

Subscribe to this mod's changes

deck-iteration-workflow is a skill published in the GitHub repository lossless-group/lossless-agent-skills (4 stars, last pushed 16d ago), licensed MIT. It adds 77 tokens to every session and 2,004 once invoked, about $0.0004 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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