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.
npx skills add latestaiagents/agent-skills --skill sub-agent-delegationgit clone --depth 1 https://github.com/latestaiagents/agent-skillsWrote 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.
[](https://agentmods.dev/skills/latestaiagents/agent-skills/sub-agent-delegation)<a href="https://agentmods.dev/skills/latestaiagents/agent-skills/sub-agent-delegation"><img src="https://agentmods.dev/badge/skills/latestaiagents/agent-skills/sub-agent-delegation/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.
<a href="https://agentmods.dev/skills/latestaiagents/agent-skills/sub-agent-delegation"><img src="https://agentmods.dev/badge/skills/latestaiagents/agent-skills/sub-agent-delegation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00096 | $0.01320 |
| Opus 5.5 | $0.00038 | $0.00528 |
| Sonnet 5.5 | $0.00019 | $0.00264 |
| Haiku 4.5 | $0.00010 | $0.00132 |
Grade A, and why
sub-agent-delegation 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sub-Agent Delegation
Sub-agents are isolated agent invocations spawned from a parent. They run in a fresh context, do focused work, and return a single result. Use them to parallelize, specialize, and protect context.
When to Use
- Parallel research (5 topics × 1 agent each, run concurrently)
- Context-heavy sub-tasks that would bloat the parent's window
- Specialist work (a "code reviewer" sub-agent, a "security auditor" sub-agent)
- Independent work items where errors shouldn't compound
When NOT to Use
- Trivial single-step tasks — sub-agent overhead isn't worth it
- Tasks that need to see the parent's full context — you'll have to pass it, defeating the isolation
- Highly interactive work — sub-agents don't ask clarifying questions back
The Model
Parent agent sees a Task (or Agent) tool. When invoked, it spawns a sub-agent with:
- A fresh conversation (no parent history)
- Its own tool set (may be a subset of parent's)
- A single prompt describing the work
- A requirement to return ONE final response
The sub-agent's intermediate tool calls are NOT visible to the parent — only the final result.
SDK Usage
import { query } from "@anthropic-ai/claude-agent-sdk";
for await (const msg of query({
prompt: "Research and compare the top 3 vector databases. Summarize pros/cons.",
options: {
model: "claude-sonnet-4-6",
allowedTools: ["Task", "WebFetch", "Read"],
},
})) { /* ... */ }
The parent agent decides to invoke Task with a prompt like "Research Pinecone's pros and cons. Use WebFetch. Report in under 200 words." Three parallel Task calls, three independent contexts, three summaries returned.
Parallel Spawning
The parent can issue multiple tool calls in one step:
Parent: Let me research all three in parallel.
[tool_use: Task] Research Pinecone...
[tool_use: Task] Research Weaviate...
[tool_use: Task] Research Qdrant...
Three sub-agents run concurrently. Parent waits for all three results, then synthesizes.
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.
- 1mo ago First seen · 151 lines · 96 tokens per session scan A 6f2440c359ac
sub-agent-delegation is a skill published in the GitHub repository latestaiagents/agent-skills (6 stars, last pushed 6mo ago), licensed MIT. It adds 96 tokens to every session and 1,320 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-03.
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