Borrowing it
Nothing to install: this file belongs to gitricko/hermes-webtop. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/gitricko/hermes-webtop/main/.agents/skills/parallel-delegation/SKILL.mdgit clone --depth 1 https://github.com/gitricko/hermes-webtopWrote 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/gitricko/hermes-webtop/parallel-delegation)<a href="https://agentmods.dev/skills/gitricko/hermes-webtop/parallel-delegation"><img src="https://agentmods.dev/badge/skills/gitricko/hermes-webtop/parallel-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/gitricko/hermes-webtop/parallel-delegation"><img src="https://agentmods.dev/badge/skills/gitricko/hermes-webtop/parallel-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 | $0.00025 | $0.01900 |
| Opus 5.5 | $0.00010 | $0.00760 |
| Sonnet 5.5 | $0.00005 | $0.00380 |
| Haiku 4.5 | $0.00003 | $0.00190 |
Grade A, and why
parallel-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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parallel Delegation
Always use as much subagent parallelism as possible: the main agent's job is orchestration, not execution. Every piece of work that a subagent can carry should be handed off, batched into the same turn, so the main agent never sits idle and the conversation keeps moving.
Core Principles
- Question every task first: can a subagent do this? If yes and it is independent of what you're doing, delegate it.
- Maximize parallelism: N independent tasks → N
delegate_taskcalls in the same assistant turn. Never spawn one at a time and never serialize independent work — sequential delegation multiplies wall-clock time for no benefit. Prefer many small, focused subagents over one big one. - Stay unblocked: between spawning and results, keep doing work that doesn't depend on the subagents. Do not hold your turn waiting for a result you don't need yet.
- Consume, don't redo: when results arrive, use them — don't re-execute the delegated work yourself.
When to Delegate
Delegate anything mechanical, long-running, parallelizable, or context-heavy:
- Batch independent audits — e.g., dependency/security/lint audits split per package or module, one subagent per scope (see Examples).
- Script runs — independent test scripts, formatting checks, or reproducible CLI commands that can run concurrently.
- Repo scans —
search_files/ codebase inspection over disjoint directories or areas, per-area. - Research & extraction — web searches, page fetches, summarization, transcript-to-summary jobs.
- Anything that doesn't need your in-flight judgment — offload it so a long-running subagent finishes by the time you need its output.
Rule of thumb: if you can enumerate the units up front, fan out one subagent per unit in a single turn.
When NOT to Delegate
- Trivial one-liners and single tool calls — a file read, a simple grep, a one-command lookup. Delegation costs tokens (~20K per spawn) and a round-trip; beating it with a single tool call is faster and cheaper.
- When you already have full context — if the answer is already in your context or you're mid-way through exactly this work, finish it yourself. Re-delegating means re-transmitting everything for nothing.
- When the task is the main agent's own judgment call — decisions, tradeoffs, or steps the conversation's next move depends on immediately.
- When spawn cost exceeds the work — one quick
web_searchstays in-thread; ten independent searches go to subagents.
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 · 197 lines · 25 tokens per session scan A 708cd56af2a2
parallel-delegation is a skill published in the GitHub repository gitricko/hermes-webtop (28 stars, last pushed 4d ago), licensed MIT. It adds 25 tokens to every session and 1,900 once invoked, about $0.0001 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 2026-10-05.
parallel-delegation compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| parallel-delegationgitricko/hermes-webtop | Skill | 28 | 4d ago | MIT | A | 25 | Claude Code, Codex |
| orca-clistablyai/orca | Skill | 117k | yesterday | MIT | A | 146 | Claude Code, Codex |
| closedavepoon/buildwithclaude | Skill | 3.7k | yesterday | MIT | A | 15 | Claude Code |
| agency-osjeremylongshore/tons-of-skills-marketplace | Skill | 2.9k | yesterday | MIT | A | 142 | Claude Code |
| atmos-custom-commandscloudposse/atmos | Skill | 1.4k | yesterday | Apache-2.0 | A | 39 | Claude Code |
| hourly-rate-timekangarooking/cangjie-skill | Skill | 12k | 1mo ago | MIT | A | 146 | Claude Code, Codex |
| workflowjeremylongshore/tons-of-skills-marketplace | Skill | 2.9k | yesterday | MIT | B | 101 | Claude Code |