diverge

diverge is a skill for Claude Code, Codex from sjarmak/coding-agent-workflows. It costs 34 tokens per session (1,307 once invoked), scanned A, original, MIT.

A research method that sends the same question to several independent agents, each exploring it from a different angle, then combines their findings into one analysis and product requirements document.

In plain words
What is it for?
Use it for technical research, comparing approaches, studying prior work, and preparing a product requirements document.
Why use it?
It reduces the risk of relying on one narrow viewpoint when investigating a difficult question. Independent work can reveal different options, evidence, and constraints.

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/sjarmak/coding-agent-workflows/diverge
Any agent
npx skills add sjarmak/coding-agent-workflows --skill diverge
Clone the repo
git clone --depth 1 https://github.com/sjarmak/coding-agent-workflows

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 diverge

README.md
[![agentmods](https://agentmods.dev/badge/skills/sjarmak/coding-agent-workflows/diverge.svg)](https://agentmods.dev/skills/sjarmak/coding-agent-workflows/diverge)
Your own site
<a href="https://agentmods.dev/skills/sjarmak/coding-agent-workflows/diverge"><img src="https://agentmods.dev/badge/skills/sjarmak/coding-agent-workflows/diverge.svg" alt="Measured on agentmods" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,307 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 $0.00034 $0.01307
Opus 5 $0.00017 $0.00654
Sonnet 5 $0.00007 $0.00261
Haiku 4.5 $0.00003 $0.00131

Measured 3d ago against content hash 116b85aad1b0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

diverge 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.

source/skills/diverge/SKILL.md · 191 lines

How it starts

The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Diverge: Multi-Perspective Divergent Research

Spawn N independent agents with uncorrelated context windows to explore a question from different angles, then auto-synthesize their findings into a unified analysis and PRD.

Arguments

[N] "research question or topic"

  • N is the number of agents (default 3, min 2, max 7).
  • The question is the research topic. Missing or unclear: ask the user to clarify before starting.

Phase 1: Frame the Research

Before spawning agents, frame the research space. Write a short research brief (3-5 bullet points) that:

  • States the core question
  • Lists known constraints or context from the conversation
  • Identifies 2-3 dimensions of exploration (e.g., technical feasibility, workflow design, prior art)

Present this to the user and confirm before proceeding. Adjust if the user gives feedback.

Phase 2: Spawn Independent Agents

Launch all N agents in parallel using the Agent tool. Each agent MUST:

  1. Have a unique research lens: assign each a distinct angle, perspective, or methodology. Examples:

    • "Prior art and industry patterns" (what exists, what others do)
    • "First-principles technical design" (bottom-up from constraints)
    • "User experience and workflow" (developer ergonomics, day-in-the-life)
    • "Failure modes and risks" (what can go wrong, edge cases)
    • "Scale and evolution" (how this grows, maintenance burden)
    • "Contrarian/devil's advocate" (challenge assumptions, explore alternatives)
  2. Receive the same research brief but with their unique lens clearly stated

  3. Be instructed to:

    • Research independently (web search, codebase exploration, reasoning)
    • Produce a structured output with: Key Findings (3-5), Concrete Recommendations (2-3), Open Questions, and a Confidence Assessment
    • NOT be told what other agents are exploring
    • Think creatively within their lens, surprising or non-obvious insights are more valuable than safe ones
  4. Use subagent_type: "general-purpose" (they need web search, file access, etc.)

Read the full file on GitHub · 191 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 · 191 lines · 34 tokens per session scan A 116b85aad1b0

Subscribe to this mod's changes

diverge is a skill published in the GitHub repository sjarmak/coding-agent-workflows (2 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 1,307 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 2026-08-31.

Related

Other skills, from other repositories

browser-trace

Capture a full DevTools-protocol trace of any browser automation — CDP firehose, screenshots, and DOM dumps — then bisect the stream into per-page searchable buckets. Use when the user wants to debug a failed run, audit network/console/DOM activity, attach a trace to an in-progress session, or feed structured per-page…

mxyhi/ok-skills · 88 tokens

planning-with-files

Manus-style persistent file-based planning for AI coding agents: keeps taskplan.md, findings.md, and progress.md on disk so work survives context loss and /clear. Use when asked to plan out, break down, or organize a multi-step project, research task, or any work requiring 5+ tool calls. Supports automatic session…

mxyhi/ok-skills · 76 tokens

ai-elements

Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.

mxyhi/ok-skills · 46 tokens

exa-search

Use Exa MCP for current web, code/docs, company, people, and page-fetch research. Prefer current hosted tool schemas and note deprecated tools.

mxyhi/ok-skills · 33 tokens

ontoly-software-graph

Use Ontoly's deterministic Software Graph and MCP capabilities for repository architecture, request tracing, dependency analysis, configuration lookup, and impact analysis before falling back to source search.

mxyhi/ok-skills · 40 tokens

product-decision-agent

中文产品决策 Agent。用于中国大陆互联网产品、运营、增长、商业化、数据、项目推进和组织协作场景:产品规划、需求分析、PRD、需求优先级、排期、版本规划、Roadmap、MVP、灰度、上线、迭代、增长停滞、拉新、投放、渠道、裂变、CAC、LTV、ROI、留存、转化、DAU/MAU、GMV、漏斗、社区运营、内容供给、创作者、用户运营、活动运营、私域、会员、定价、指标异常、数据口径、埋点、A/B…

mxyhi/ok-skills · 265 tokens