Automated summary
Creates and manages multi-step AI workflows by defining, implementing, and improving DeepWork jobs.
Strengths
- Automates complex processes through chained steps
- Interactive job specification generation
- Learns from conversations to refine instructions
- Uses Skill tool to prevent copy-paste errors
Limitations
- Requires prior understanding of DeepWork workflows
- Depends on the Skill tool for correct execution
- Can be rigid if steps must follow a fixed order
Use this skill when you need to define a new multi-step workflow or improve an existing job based on execution feedback.
Do not use for simple one-step tasks or when you want to run an isolated command without workflow structure.
Security analysis
SafeThe skill orchestrates workflow management through a defined Skill tool, with no direct execution of dangerous commands or external system access. It does not instruct destructive actions, exfiltration, or obfuscation. The risk is minimal as it only guides users through creating and improving job specifications.
No concerns found
How this analysis is madeExamples
/deepwork_jobs define I need a workflow that first scans a codebase for TODOs, then generates a report, and finally creates issues in a tracker./deepwork_jobs learn Review the last conversation where we ran the 'report_gen' job and improve its instructions./deepwork_jobs implement Generate the step instruction files for the job spec I just defined.name: deepwork_jobs description: "Creates and manages multi-step AI workflows. Use when defining, implementing, or improving DeepWork jobs."
deepwork_jobs
Multi-step workflow: Creates and manages multi-step AI workflows. Use when defining, implementing, or improving DeepWork jobs.
CRITICAL: Always invoke steps using the Skill tool. Never copy/paste step instructions directly.
Core commands for managing DeepWork jobs. These commands help you define new multi-step workflows and learn from running them.
The define command guides you through an interactive process to create a new job by
asking structured questions about your workflow, understanding each step's inputs and outputs,
and generating all necessary files.
The learn command reflects on conversations where DeepWork jobs were run, identifies
confusion or inefficiencies, and improves job instructions. It also captures bespoke
learnings specific to the current run into AGENTS.md files in the working folder.
Available Steps
- define - Creates a job.yml specification by gathering workflow requirements through structured questions. Use when starting a new multi-step workflow.
- review_job_spec - Reviews job.yml against quality criteria using a sub-agent for unbiased validation. Use after defining a job specification. (requires: define)
- implement - Generates step instruction files and syncs slash commands from the job.yml specification. Use after job spec review passes. (requires: review_job_spec)
- learn - Analyzes conversation history to improve job instructions and capture learnings. Use after running a job to refine it.
Execution Instructions
Step 1: Analyze Intent
Parse any text following /deepwork_jobs to determine user intent:
- "define" or related terms → start at
deepwork_jobs.define - "review_job_spec" or related terms → start at
deepwork_jobs.review_job_spec - "implement" or related terms → start at
deepwork_jobs.implement - "learn" or related terms → start at
deepwork_jobs.learn
Step 2: Invoke Starting Step
Use the Skill tool to invoke the identified starting step:
Skill tool: deepwork_jobs.define
Step 3: Continue Workflow Automatically
After each step completes:
- Check if there's a next step in the sequence
- Invoke the next step using the Skill tool
- Repeat until workflow is complete or user intervenes
Handling Ambiguous Intent
If user intent is unclear, use AskUserQuestion to clarify:
- Present available steps as numbered options
- Let user select the starting point
Guardrails
- Do NOT copy/paste step instructions directly; always use the Skill tool to invoke steps
- Do NOT skip steps in the workflow unless the user explicitly requests it
- Do NOT proceed to the next step if the current step's outputs are incomplete
- Do NOT make assumptions about user intent; ask for clarification when ambiguous
Context Files
- Job definition:
.deepwork/jobs/deepwork_jobs/job.yml
From the file to a first result
The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.
View the source and supporting filesThis download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.
1. Download the file
Download SKILL.mdFrom the root of a test project, save the file as .skill-downloads/deepwork-jobs-management-mm5t8a7s/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.
Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.
mkdir -p '.skill-downloads/deepwork-jobs-management-mm5t8a7s' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/deepwork-jobs-management-mm5t8a7s/download' --output '.skill-downloads/deepwork-jobs-management-mm5t8a7s/SKILL.md.part' && mv '.skill-downloads/deepwork-jobs-management-mm5t8a7s/SKILL.md.part' '.skill-downloads/deepwork-jobs-management-mm5t8a7s/SKILL.md'2. Check prerequisites
Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.
No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.
The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.
3. Load the skill
This file does not provide a usable name/description header for this native procedure. It remains available to download and inspect; use the manual method below.
Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.
4. Try a first task
Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:
Read .skill-downloads/deepwork-jobs-management-mm5t8a7s/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.
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