to-epics

to-epics is a skill for Claude Code, Codex from Future-CX/AI-Architecture-Toolkit. It costs 100 tokens per session (2,307 once invoked), scanned A, original, MIT.

A workflow for turning an approved target architecture into reviewable epics. A target architecture describes the intended structure of a software system, while an epic is a large piece of work made up of related tasks.

In plain words
What is it for?
Splitting planned architecture changes into named epics, checking their terms against a glossary, and recording them in the architecture document's building-blocks phase.
Why use it?
It helps ensure architecture work is clarified, uses consistent terminology, and is divided into units that can be reviewed and implemented. It requires key details before creating an epic file.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is ### [{{EPIC_NAME}}](../../requirements/{{TARGET_ARCHITECTURE_NAME}}/{{EPIC_SLUG}}.md).

Good fit Splitting planned architecture changes into named epics, checking their terms against a glossary, and recording them in the architecture document's building-blocks phase.

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Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/Future-CX/AI-Architecture-Toolkit
agentmods
npx agentmods add skills/future-cx/ai-architecture-toolkit/to-epics

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 to-epics

README.md
[![agentmods](https://agentmods.dev/badge/skills/future-cx/ai-architecture-toolkit/to-epics/github.svg)](https://agentmods.dev/skills/future-cx/ai-architecture-toolkit/to-epics)
Your own site
<a href="https://agentmods.dev/skills/future-cx/ai-architecture-toolkit/to-epics"><img src="https://agentmods.dev/badge/skills/future-cx/ai-architecture-toolkit/to-epics/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 to-epics

Your own site · 80×15
<a href="https://agentmods.dev/skills/future-cx/ai-architecture-toolkit/to-epics"><img src="https://agentmods.dev/badge/skills/future-cx/ai-architecture-toolkit/to-epics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 100 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,307 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 $0.00100 $0.02307
Opus 5 $0.00050 $0.01154
Sonnet 5 $0.00020 $0.00461
Haiku 4.5 $0.00010 $0.00231

Measured 5d ago against content hash c588bcfba7d3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

to-epics 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 5d 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.

skills/to-epics/SKILL.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

To Epics

Quick Start

Use this skill after a target architecture document exists or when the user explicitly wants architecture work translated into epics.

Do not automatically create epics from analysis alone. Before creating or updating an epic file, require the user to provide:

  • Target architecture to link to
  • Epic name
  • Phase
  • Epic description
  • Main capability

If any required input is missing, ask for it and stop before writing the epic.

Output Location

Create epics in the private lab root under requirements/<name-of-target-architecture>/.

Use the target architecture folder name as <name-of-target-architecture> unless the target architecture document defines a clearer document name. Normalize it to the same slug style used for folders.

<private-lab-root>/
├── requirements/
│   └── <target-architecture-slug>/
│       └── <epic-slug>.md
└── solution-architectures/
    └── <target-architecture-slug>/
        ├── 08-phase-e-solution-building-blocks.md
        └── target-architecture-document.md

Use templates/epic-template.md for the epic file. Preserve the two opening tables: the document metadata table first, followed by the Epic Overview table.

Workflow

  1. Ask the user which target architecture to link the epic to.
    • If the user named a target architecture, confirm the exact folder or document path before continuing.
    • If the user did not name one, search for solution-architectures/*/target-architecture-document.md, present the candidates, and ask the user to choose.
    • Do not create an epic until the user has selected or confirmed the target architecture linkage.
  2. Read the target architecture document and relevant section files, especially 08-phase-e-solution-building-blocks.md, roadmap themes, gap analysis, governance actions, risks, and open questions.
  3. Ask the user for the epic name, phase, epic description, and main capability if not already provided.
  4. Ask for reference links:
    • Main capability link
    • Main L2 solution architecture link
    • Existing Jira item URL/key, if any
    • Existing Confluence page URL, if any These references are optional except when the user can identify the linked artifact. Use TBD when the user does not provide a link. Use the linked document title as the Markdown link label whenever possible. For local markdown files, derive the title from the first # heading; otherwise use the filename without extension. For Jira and Confluence links, use the issue key/page title when the user provides it; otherwise ask for the title or use TBD.
  5. Start a grill-me clarification session using ../grill-me/SKILL.md.
    • Focus the session on whether the epic has enough detail to be useful for delivery planning.
    • Ask one question at a time and wait for the user's answer before continuing.
    • Cover scope, out of scope, assumptions, dependencies, business requirements, visual design, solution design, Site Reliability Engineering, architecture impact, open questions, and glossary-sensitive terminology.
    • Use ../ubiquitous-language/SKILL.md during the session when terms are vague, overloaded, missing from GLOSSARY.md, or important enough to become shared domain language.
    • Continue only when the required epic fields are confirmed and remaining unknowns are explicitly captured as open questions or TBD.
  6. Confirm the target architecture linkage:
    • Target architecture document path
    • Requirements output folder: <private-lab-root>/requirements/<name-of-target-architecture>/
    • Phase
    • Main capability
    • Main capability link, or TBD
    • Main capability link title, derived from the linked capability document title where possible
    • Main L2 solution architecture link, or TBD
    • Main L2 solution architecture link title, derived from the linked solution architecture document title where possible
    • Jira item reference, if provided
    • Jira link title, normally the issue key or issue summary
    • Confluence page reference, if provided
    • Confluence link title, normally the page title
    • Roadmap theme, gap, decision, governance action, or architecture section the epic supports
    • Any known dependencies or sequencing constraints
  7. Validate terminology before writing the epic:
    • Locate <private-lab-root>/GLOSSARY.md.
    • Check the epic name, description, main capability, scope terms, application names, data objects, integrations, and business requirements against the glossary.
    • If GLOSSARY.md is missing, or if important terms are missing, ambiguous, or inconsistent, use ../ubiquitous-language/SKILL.md to create or update <private-lab-root>/GLOSSARY.md before creating the epic.
    • Do not write real-company terminology into this public toolkit repository; update the private lab root glossary.
  8. Create requirements/<name-of-target-architecture>/<epic-slug>.md from the template. Preserve the document metadata table and the Epic Overview table. Do not overwrite an existing epic unless the user explicitly asks to update it.
  9. Update the target architecture linkage:
    • Add or update the epic's titled block in the ## Epics To Build section of 08-phase-e-solution-building-blocks.md when that file exists.
    • Add or update the same titled block in a ### Epics To Build subsection of the Phase E section in target-architecture-document.md when that subsection exists.
    • Link the epic file with a relative markdown link from the target architecture document folder to the requirements file.
  10. Summarize what was created, which grill-me questions materially shaped the epic, which glossary terms were confirmed or added, and which target architecture sections the epic traces to.

Read the full file on GitHub · 172 lines

Files

What ships with it

2 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. 5d ago Changed · +4 lines c588bcfba7d3
  2. 9d ago First seen · 168 lines · 100 tokens per session scan A 9f0f77adce33

Subscribe to this mod's changes

to-epics is a skill published in the GitHub repository Future-CX/AI-Architecture-Toolkit (5 stars, last pushed 5d ago), licensed MIT. It adds 100 tokens to every session and 2,307 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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