shell-agent-delegation

shell-agent-delegation is a skill for Claude Code, Codex from HKUDS/OpenSpace. It costs 25 tokens per session (840 once invoked), scanned A, original, MIT.

A fallback workflow for handing complex tasks to an autonomous shell-based agent when direct tools fail.

In plain words
What is it for?
Use it for multi-step coding, data-processing, or document-generation tasks that direct execution cannot complete.
Why use it?
It helps continue work after repeated tool errors by letting the agent choose commands or libraries, retry failures, and adapt its approach.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for multi-step coding, data-processing, or document-generation tasks that direct execution cannot complete.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hkuds/openspace/shell-agent-delegation
About the project

OpenSpace is a skill-management layer for AI agents that stores, retrieves, evaluates, shares, and improves reusable workflows. It is intended for people using multiple coding agents who want skills to be reused and refined based on task outcomes. The catalogue provides 200 skills for use with OpenSpace and the agents it supports.

HKUDS/OpenSpace · 7,544 stars · on GitHub

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 HKUDS/OpenSpace --skill shell-agent-delegation
Clone the repo
git clone --depth 1 https://github.com/HKUDS/OpenSpace

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 shell-agent-delegation

README.md
[![agentmods](https://agentmods.dev/badge/skills/hkuds/openspace/shell-agent-delegation.svg)](https://agentmods.dev/skills/hkuds/openspace/shell-agent-delegation)
Your own site
<a href="https://agentmods.dev/skills/hkuds/openspace/shell-agent-delegation"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/shell-agent-delegation.svg" alt="Measured on agentmods" height="20"></a>
Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 840 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 pass 7 Sept 2026
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 $0.00025 $0.00840
Opus 5 $0.00013 $0.00420
Sonnet 5 $0.00005 $0.00168
Haiku 4.5 $0.00003 $0.00084

Measured 5d ago against content hash 3bdf8ae24c83, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

shell-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 5d 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.

benchmarks/gdpval/skills/shell-agent-delegation/SKILL.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Shell Agent Delegation for Resilient Workflow Execution

When to Use This Skill

Apply this pattern when:

  • Direct tool execution (execute_code_sandbox, read_webpage, search_web) fails with 'unknown error'
  • Multiple tool attempts have failed in sequence
  • The task requires complex document generation or data processing
  • You need a tool that can autonomously select libraries and handle multi-step workflows

Why This Works

The shell_agent tool differs from direct execution tools in key ways:

  • Autonomous tool selection: Decides whether to use Python or Bash based on the task
  • Built-in error recovery: Automatically retries and fixes errors (up to several rounds)
  • Iterative execution: Writes code, executes, inspects output, and adapts
  • Full workflow ownership: Handles the entire task end-to-end without manual intervention

Step-by-Step Instructions

Step 1: Recognize the Failure Pattern

Identify when to pivot to shell_agent:

- execute_code_sandbox returned 'unknown error'
- read_webpage/search_web failed multiple times
- Direct approaches are struggling with the task complexity

Step 2: Formulate the Delegation Task

Create a clear, self-contained task description for shell_agent:

Good task description:

Create a 1-page SBAR Template PDF document. Include sections for:
- Situation: Brief description of the current situation
- Background: Relevant context and history
- Assessment: Current assessment and analysis
- Recommendation: Proposed actions and next steps
Use a professional layout with clear headings and adequate whitespace.

Key elements to include:

  • The end goal (what should be produced)
  • Required sections/components
  • Format requirements (PDF, DOCX, etc.)
  • Any style or layout preferences

Step 3: Execute the Delegation

Call shell_agent with your task description:

# Conceptual example
shell_agent(task="Create a professional SBAR Template PDF with Situation, Background, Assessment, and Recommendation sections. Include clear headings and professional formatting.")

Read the full file on GitHub · 108 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 5d ago First seen · 108 lines · 25 tokens per session scan A 3bdf8ae24c83

Subscribe to this mod's changes

shell-agent-delegation is a skill published in the GitHub repository HKUDS/OpenSpace (7,544 stars, last pushed 26d ago), licensed MIT. It adds 25 tokens to every session and 840 once invoked, about $0.0001 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 2026-09-03.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens