orchestrating-fusion

orchestrating-fusion is a skill for Claude Code from jellydn/my-ai-tools. It costs 37 tokens per session (1,199 once invoked), scanned A, original, MIT.

A coordination method that separates investigation and technical decisions from code changes. One agent prepares a bounded specification, another carries out the implementation, and the work is independently checked.

In plain words
What is it for?
Use it for changes that need architectural judgment, several edits, a written implementation plan, or separate verification.
Why use it?
It reduces the chance that the same process both makes and approves important technical decisions, especially on non-trivial coding tasks.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: mentions subagents; mentions Codex; built for cline.

Good fit Use it for changes that need architectural judgment, several edits, a written implementation plan, or separate verification.

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Install with agentmods
npx agentmods add skills/jellydn/my-ai-tools/orchestrating-fusion
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 jellydn/my-ai-tools --skill orchestrating-fusion
Clone the repo
git clone --depth 1 https://github.com/jellydn/my-ai-tools

Made for: Claude Code.

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 orchestrating-fusion

README.md
[![agentmods](https://agentmods.dev/badge/skills/jellydn/my-ai-tools/orchestrating-fusion/github.svg)](https://agentmods.dev/skills/jellydn/my-ai-tools/orchestrating-fusion)
Your own site
<a href="https://agentmods.dev/skills/jellydn/my-ai-tools/orchestrating-fusion"><img src="https://agentmods.dev/badge/skills/jellydn/my-ai-tools/orchestrating-fusion/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 orchestrating-fusion

Your own site · 80×15
<a href="https://agentmods.dev/skills/jellydn/my-ai-tools/orchestrating-fusion"><img src="https://agentmods.dev/badge/skills/jellydn/my-ai-tools/orchestrating-fusion.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,199 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 warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Rogue Agent · line 22
    Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
    Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 $0.00037 $0.01199
Opus 5 $0.00018 $0.00600
Sonnet 5 $0.00007 $0.00240
Haiku 4.5 $0.00004 $0.00120

Measured 13d ago against content hash 6deb8d5396cc, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

orchestrating-fusion 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 13d 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.

configs/amp/plugins/my-ai-tools-skills/skills/orchestrating-fusion/SKILL.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Fusion Orchestration

Separate judgment from mechanical implementation. A lead investigates, decides, specifies, reviews, and verifies. An executor edits only the bounded scope in the lead's specification.

Route Deliberately

Do not force every task through Fusion:

  • Keep a tiny, already-understood, single-file mechanical change in the normal writable session.
  • Use Fusion when investigation, architectural judgment, multiple non-trivial writes, or independent review materially improve the result.
  • Offer a durable PRD, ADR, or implementation plan only when persistent artifacts reduce substantial ambiguity. Never create a spec lifecycle merely because a change is large or risky.

Native Adapters

Prefer the installed native roles when the current tool exposes them:

  • OpenCode: run the fusion-lead primary; it can delegate to fusion-executor and cannot edit or run shell commands.
  • Amp: select the fusion agent mode; its restricted tool surface exposes fusion_executor for implementation.
  • Codex: from the writable root session, spawn fusion-lead for the specification, then spawn the sibling fusion-executor; a read-only child cannot safely escalate a nested child to workspace-write.
  • Pi: from the root session, use the Agent tool to run fusion-lead, then run the sibling fusion-executor; pi-subagents enforces the lead's tool allowlist and intentionally disables nested delegation.

For other assistants, apply the workflow below using their native subagent/task tool. Treat role separation as advisory unless the harness actually restricts each role's tools or sandbox.

Workflow

  1. Have the lead inspect the request and relevant code. It may delegate read-only discovery.
  2. The lead resolves architectural and product choices. Ask the user only when a missing decision materially changes the result.
  3. The lead selects only the relevant installed skills. Include each exact SKILL.md path in the handoff; do not paraphrase a skill into a lossy substitute or preload unrelated skills.
  4. The lead sends the executor one bounded specification using this contract. Keep specifications concise (target under 2,000 tokens) — summarize objectives succinctly and reference skill paths, rather than pasting full PRDs, raw user prompts, or file contents verbatim. When the harness prevents nested delegation, the lead returns this specification to the writable root, which starts the executor as a sibling:

Read the full file on GitHub · 86 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. 13d ago First seen · 86 lines · 37 tokens per session scan A 6deb8d5396cc

Subscribe to this mod's changes

orchestrating-fusion is a skill published in the GitHub repository jellydn/my-ai-tools (120 stars, last pushed today), licensed MIT. It adds 37 tokens to every session and 1,199 once invoked, about $0.0002 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.