ddd-distribute

ddd-distribute is a skill for Claude Code, Codex from xg-gh-25/SwarmAI. It costs 209 tokens per session (1,218 once invoked), scanned A, original, MIT.

A packaging step that turns a completed DDD into a capability package for another agent host, such as Kiro, Quick, or Claude Code.

In plain words
What is it for?
Use it to choose declared distribution targets, build the package, and review warnings and its output path.
Why use it?
It prevents packages from being produced for targets or visibility levels that the DDD owner has not declared.

Skill for Claude CodeCodex

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

Good fit Use it to choose declared distribution targets, build the package, and review warnings and its output path.

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Install with agentmods
npx agentmods add skills/xg-gh-25/swarmai/s_ddd-distribute
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 xg-gh-25/SwarmAI --skill s_ddd-distribute
Clone the repo
git clone --depth 1 https://github.com/xg-gh-25/SwarmAI

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 ddd-distribute

README.md
[![agentmods](https://agentmods.dev/badge/skills/xg-gh-25/swarmai/s_ddd-distribute/github.svg)](https://agentmods.dev/skills/xg-gh-25/swarmai/s_ddd-distribute)
Your own site
<a href="https://agentmods.dev/skills/xg-gh-25/swarmai/s_ddd-distribute"><img src="https://agentmods.dev/badge/skills/xg-gh-25/swarmai/s_ddd-distribute/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 ddd-distribute

Your own site · 80×15
<a href="https://agentmods.dev/skills/xg-gh-25/swarmai/s_ddd-distribute"><img src="https://agentmods.dev/badge/skills/xg-gh-25/swarmai/s_ddd-distribute.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 209 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,218 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00209 $0.01218
Opus 5 $0.00105 $0.00609
Sonnet 5 $0.00042 $0.00244
Haiku 4.5 $0.00021 $0.00122

Measured today against content hash 0b66e4a60667, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

ddd-distribute 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 today.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/distribute.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

backend/skills/s_ddd-distribute/SKILL.md · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DDD Distribute (s_ddd-distribute) — the distribution step of the DDD lifecycle

Render a grown DDD into a distributable capability package so another agent host (Kiro / Quick / Claude Code / a public consumer) can install and use it.

This skill is a thin human-in-the-loop wrapper — all packaging logic lives in core/ddd_packager.py and the reach policy in core/ddd_distribution_policy.py. The skill's job is: read the declaration → confirm the target subset with the human → call the packager → surface warnings and the built path.

The reach model (READ BEFORE RUNNING)

A DDD declares its own reach in its aim.json:

"distribution": {
  "targets": ["aim-capabilities", "open-plugin"],   // the CEILING (0..2)
  "visibility": "internal"                            // internal | external
}
  • The declaration is the ceiling. You may emit a SUBSET of the declared targets; you may NEVER add an undeclared target or raise visibility. To widen reach, the DDD owner edits the declaration first (a separate, deliberate change).
  • Fail-closed. An absent / malformed declaration → targets:[] = not distributable. Nothing leaves by inference.
  • Emit ≠ publish. A visibility:internal DDD may EMIT an open-plugin tree for a private install, but the public-publish step is refused until visibility is explicitly external (a human-gated change).

Workflow (HITL)

  1. Locate the DDD — resolve <workspace>/Projects/<name>/ (the DDD dir).
  2. Read the declaration — call the packager's policy; show the human the declared targets + visibility + any warnings (e.g. an unknown target token).
  3. Confirm the subset — ask the human WHICH declared target(s) to emit now, and whether this is an emit-only pass or an external publish. Never propose a target the DDD didn't declare.
  4. Render — run scripts/distribute.py with the confirmed subset. The packager: emits each target tree, runs the content-safety scan over the EMITTED tree, and aborts (fail-closed) on any secret / host-path (any target) or internal-string (external publish).
  5. Return the path(s) — report the built package dir(s) + any scan warnings + which skills were included (class-B domain) vs excluded (class-A enablement / unclassified). Point the human at the install command:
    • internal → build + cr/PR into the internal package, then aim plugins install <Pkg>
    • external → push to the public code host, then aim plugins install / bash install.sh

Read the full file on GitHub · 81 lines

Files

What ships with it

1 file 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. today Changed · +10 lines 0b66e4a60667
  2. 13d ago First seen · 71 lines · 209 tokens per session scan A c4577cad57c7

Subscribe to this mod's changes

ddd-distribute is a skill published in the GitHub repository xg-gh-25/SwarmAI (44 stars, last pushed yesterday), licensed MIT. It adds 209 tokens to every session and 1,218 once invoked, about $0.0010 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 2026-08-30.