parallel-agents

A guide to coordinating multiple coding agents on larger tasks. It describes assigning different agents to areas such as security, performance, architecture, backend, frontend, or testing, then passing findings between them.

In plain words
What is it for?
Use it for broad code reviews, security and performance analysis, or features spanning backend, frontend, and databases. It supports single-agent work, sequential reviews, context sharing, and resuming previous work.
Why use it?
It helps divide work that needs several kinds of expertise and combine the results in a planned sequence. It also identifies cases where one agent is enough.

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/diillson/chatcli/parallel-agents
Any agent
npx skills add diillson/chatcli --skill parallel-agents
Clone the repo
git clone --depth 1 https://github.com/diillson/chatcli

Made for: Claude Code, Codex.

Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,273 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 89% copy Near-identical to another mod 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 $0.00029 $0.01273
Opus 5 $0.00015 $0.00636
Sonnet 5 $0.00006 $0.00255
Haiku 4.5 $0.00003 $0.00127

Measured 2d ago against content hash a623844590ef, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

parallel-agents 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 2d 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.

Origin

This is a copy

89% identical to parallel-agents — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agent/skills/parallel-agents/SKILL.md · 176 lines

How it starts

The opening of the file, as written. The whole thing — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Native Parallel Agents

Orchestration through Antigravity's built-in Agent Tool

Overview

This skill enables coordinating multiple specialized agents through Antigravity's native agent system. Unlike external scripts, this approach keeps all orchestration within Antigravity's control.

When to Use Orchestration

Good for:

  • Complex tasks requiring multiple expertise domains
  • Code analysis from security, performance, and quality perspectives
  • Comprehensive reviews (architecture + security + testing)
  • Feature implementation needing backend + frontend + database work

Not for:

  • Simple, single-domain tasks
  • Quick fixes or small changes
  • Tasks where one agent suffices

Native Agent Invocation

Single Agent

Use the security-auditor agent to review authentication

Sequential Chain

First, use the explorer-agent to discover project structure.
Then, use the backend-specialist to review API endpoints.
Finally, use the test-engineer to identify test gaps.

With Context Passing

Use the frontend-specialist to analyze React components.
Based on those findings, have the test-engineer generate component tests.

Resume Previous Work

Resume agent [agentId] and continue with additional requirements.

Orchestration Patterns

Pattern 1: Comprehensive Analysis

Agents: explorer-agent → [domain-agents] → synthesis

1. explorer-agent: Map codebase structure
2. security-auditor: Security posture
3. backend-specialist: API quality
4. frontend-specialist: UI/UX patterns
5. test-engineer: Test coverage
6. Synthesize all findings

Pattern 2: Feature Review

Agents: affected-domain-agents → test-engineer

1. Identify affected domains (backend? frontend? both?)
2. Invoke relevant domain agents
3. test-engineer verifies changes
4. Synthesize recommendations

Pattern 3: Security Audit

Agents: security-auditor → penetration-tester → synthesis

1. security-auditor: Configuration and code review
2. penetration-tester: Active vulnerability testing
3. Synthesize with prioritized remediation

Read the full file on GitHub · 176 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. 2d ago First seen · 176 lines · 29 tokens per session scan A a623844590ef

Subscribe to this mod's changes

parallel-agents is a skill published in the GitHub repository diillson/chatcli (89 stars, last pushed 3d ago), licensed Apache-2.0. It adds 29 tokens to every session and 1,273 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to parallel-agents, differing in 8 lines, and is treated as a copy.