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doc updates and deepwork sync results
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.claude/commands/deepwork_jobs.define.md

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Verify the job.yml output meets ALL quality criteria before completing:
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1. **User Understanding**: Did you fully understand the user's workflow by asking structured questions?
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2. **Structured Questions Used**: Did you ask structured questions (using the AskUserQuestion tool) to gather user input?
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3. **Clear Inputs/Outputs**: Does every step have clearly defined inputs and outputs?
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4. **Logical Dependencies**: Do step dependencies make sense and avoid circular references?
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5. **Concise Summary**: Is the summary under 200 characters and descriptive?
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6. **Rich Description**: Does the description provide enough context for future refinement?
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7. **Valid Schema**: Does the job.yml follow the required schema (name, version, summary, steps)?
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8. **File Created**: Has the job.yml file been created in `.deepwork/jobs/[job_name]/job.yml`?
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1. **User Understanding**: Did you fully understand the user's workflow through interactive Q&A?
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2. **Clear Inputs/Outputs**: Does every step have clearly defined inputs and outputs?
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3. **Logical Dependencies**: Do step dependencies make sense and avoid circular references?
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4. **Concise Summary**: Is the summary under 200 characters and descriptive?
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5. **Rich Description**: Does the description provide enough context for future refinement?
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6. **Valid Schema**: Does the job.yml follow the required schema (name, version, summary, steps)?
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7. **File Created**: Has the job.yml file been created in `.deepwork/jobs/[job_name]/job.yml`?
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If ANY criterion is not met, continue working to address it.
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If ALL criteria are satisfied, include `<promise>✓ Quality Criteria Met</promise>` in your response.
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workflows and learn from running them.
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The `define` command guides you through an interactive process to create a new job by
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asking structured questions about your workflow, understanding each step's inputs and outputs,
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asking detailed questions about your workflow, understanding each step's inputs and outputs,
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and generating all necessary files.
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The `learn` command reflects on conversations where DeepWork jobs were run, identifies
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## Task
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Guide the user through defining a job specification by asking structured questions. **Do not attempt to create the specification without first fully understanding the user's needs.**
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**Important**: Use the AskUserQuestion tool to ask structured questions when gathering information from the user. This provides a better user experience with clear options and guided choices.
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Guide the user through defining a job specification by asking clarifying questions. **Do not attempt to create the specification without first fully understanding the user's needs.**
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The output of this step is **only** the `job.yml` file - a complete specification of the workflow. The actual step instruction files will be created in the next step (`implement`).
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### Step 1: Understand the Job Purpose
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Start by asking structured questions to understand what the user wants to accomplish:
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Start by asking questions to understand what the user wants to accomplish:
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1. **What is the overall goal of this workflow?**
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- What complex task are they trying to accomplish?
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### Step 2: Define Each Step
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For each major phase they mentioned, ask structured questions to gather details:
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For each major phase they mentioned, ask detailed questions:
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1. **Step Purpose**
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- What exactly does this step accomplish?
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For each step, consider whether it would benefit from **quality validation loops**. Stop hooks allow the AI agent to iteratively refine its work until quality criteria are met.
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**Ask structured questions about quality validation:**
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**Ask the user about quality validation:**
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- "Are there specific quality criteria that must be met for this step?"
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- "Would you like the agent to validate its work before completing?"
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- "What would make you send the work back for revision?"
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## Important Guidelines
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1. **Focus on specification only** - Don't create instruction files yet
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2. **Ask structured questions** - Never skip the discovery phase; use the AskUserQuestion tool
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2. **Ask clarifying questions** - Never skip the discovery phase
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3. **Rich context in description** - This helps with future refinement
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4. **Validate understanding** - Summarize and confirm before creating
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5. **Use examples** - Help users understand what good specifications look like
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6. **Understand file organization** - Always ask structured questions about where outputs should be saved and if subdirectories are needed
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6. **Understand file organization** - Always ask where outputs should be saved and if subdirectories are needed
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## Validation Rules
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## Quality Criteria
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- Asked structured questions to fully understand user requirements
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- User fully understands what job they're creating
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- All steps have clear inputs and outputs
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- Dependencies make logical sense
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### Quality Criteria
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Verify the job.yml output meets ALL quality criteria before completing:
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1. **User Understanding**: Did you fully understand the user's workflow by asking structured questions?
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2. **Structured Questions Used**: Did you ask structured questions (using the AskUserQuestion tool) to gather user input?
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3. **Clear Inputs/Outputs**: Does every step have clearly defined inputs and outputs?
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4. **Logical Dependencies**: Do step dependencies make sense and avoid circular references?
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5. **Concise Summary**: Is the summary under 200 characters and descriptive?
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6. **Rich Description**: Does the description provide enough context for future refinement?
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7. **Valid Schema**: Does the job.yml follow the required schema (name, version, summary, steps)?
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8. **File Created**: Has the job.yml file been created in `.deepwork/jobs/[job_name]/job.yml`?
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1. **User Understanding**: Did you fully understand the user's workflow through interactive Q&A?
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2. **Clear Inputs/Outputs**: Does every step have clearly defined inputs and outputs?
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3. **Logical Dependencies**: Do step dependencies make sense and avoid circular references?
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4. **Concise Summary**: Is the summary under 200 characters and descriptive?
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5. **Rich Description**: Does the description provide enough context for future refinement?
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6. **Valid Schema**: Does the job.yml follow the required schema (name, version, summary, steps)?
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7. **File Created**: Has the job.yml file been created in `.deepwork/jobs/[job_name]/job.yml`?
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If ANY criterion is not met, continue working to address it.
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If ALL criteria are satisfied, include `<promise>✓ Quality Criteria Met</promise>` in your response.

.claude/commands/deepwork_jobs.implement.md

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3. **Specific & Actionable**: Are instructions tailored to each step's purpose, not generic?
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4. **Output Examples**: Does each instruction file show what good output looks like?
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5. **Quality Criteria**: Does each instruction file define quality criteria for its outputs?
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6. **Ask Structured Questions**: Do step instructions that gather user input explicitly use the phrase "ask structured questions"?
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7. **Sync Complete**: Has `deepwork sync` been run successfully?
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8. **Commands Available**: Are the slash-commands generated in `.claude/commands/`?
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9. **Policies Considered**: Have you thought about whether policies would benefit this job?
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6. **Sync Complete**: Has `deepwork sync` been run successfully?
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7. **Commands Available**: Are the slash-commands generated in `.claude/commands/`?
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8. **Policies Considered**: Have you thought about whether policies would benefit this job?
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- If relevant policies were identified, did you explain them and offer to run `/deepwork_policy.define`?
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- Not every job needs policies - only suggest when genuinely helpful.
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workflows and learn from running them.
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The `define` command guides you through an interactive process to create a new job by
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asking structured questions about your workflow, understanding each step's inputs and outputs,
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asking detailed questions about your workflow, understanding each step's inputs and outputs,
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and generating all necessary files.
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The `learn` command reflects on conversations where DeepWork jobs were run, identifies
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4. **Explain the "why"** - Help the user understand the step's role in the workflow
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5. **Quality over quantity** - Detailed, actionable instructions are better than vague ones
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6. **Align with stop hooks** - If the step has `stop_hooks` defined, ensure the quality criteria in the instruction file match the validation criteria in the hooks
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7. **Ask structured questions** - When a step has user inputs, the instructions MUST explicitly tell the agent to "ask structured questions" using the AskUserQuestion tool to gather that information. Never use generic phrasing like "ask the user" - always use "ask structured questions"
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### Handling Stop Hooks
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- Instructions are specific and actionable
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- Output examples are provided in each instruction file
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- Quality criteria defined for each step
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- Steps with user inputs explicitly use "ask structured questions" phrasing
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- Sync completed successfully
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- Commands available for use
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- Thoughtfully considered relevant policies for the job domain
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3. **Specific & Actionable**: Are instructions tailored to each step's purpose, not generic?
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4. **Output Examples**: Does each instruction file show what good output looks like?
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5. **Quality Criteria**: Does each instruction file define quality criteria for its outputs?
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6. **Ask Structured Questions**: Do step instructions that gather user input explicitly use the phrase "ask structured questions"?
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7. **Sync Complete**: Has `deepwork sync` been run successfully?
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8. **Commands Available**: Are the slash-commands generated in `.claude/commands/`?
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9. **Policies Considered**: Have you thought about whether policies would benefit this job?
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6. **Sync Complete**: Has `deepwork sync` been run successfully?
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7. **Commands Available**: Are the slash-commands generated in `.claude/commands/`?
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8. **Policies Considered**: Have you thought about whether policies would benefit this job?
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- If relevant policies were identified, did you explain them and offer to run `/deepwork_policy.define`?
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- Not every job needs policies - only suggest when genuinely helpful.
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.claude/commands/deepwork_jobs.learn.md

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workflows and learn from running them.
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The `define` command guides you through an interactive process to create a new job by
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asking structured questions about your workflow, understanding each step's inputs and outputs,
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asking detailed questions about your workflow, understanding each step's inputs and outputs,
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and generating all necessary files.
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The `learn` command reflects on conversations where DeepWork jobs were run, identifies

.claude/commands/deepwork_policy.define.md

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## Task
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Guide the user through defining a new policy by asking structured questions. **Do not create the policy without first understanding what they want to enforce.**
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**Important**: Use the AskUserQuestion tool to ask structured questions when gathering information from the user. This provides a better user experience with clear options and guided choices.
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Guide the user through defining a new policy by asking clarifying questions. **Do not create the policy without first understanding what they want to enforce.**
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### Step 1: Understand the Policy Purpose
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Start by asking structured questions to understand what the user wants to enforce:
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Start by asking questions to understand what the user wants to enforce:
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1. **What guideline or constraint should this policy enforce?**
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## Quality Criteria
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- Asked structured questions to understand user requirements
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- Policy name is clear and descriptive
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- Trigger patterns accurately match the intended files
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- Safety patterns prevent unnecessary triggering

.deepwork/jobs/deepwork_jobs/job.yml

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name: deepwork_jobs
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version: "0.5.0"
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version: "0.4.0"
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summary: "DeepWork job management commands"
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description: |
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Core commands for managing DeepWork jobs. These commands help you define new multi-step
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workflows and learn from running them.
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The `define` command guides you through an interactive process to create a new job by
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asking structured questions about your workflow, understanding each step's inputs and outputs,
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asking detailed questions about your workflow, understanding each step's inputs and outputs,
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and generating all necessary files.
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changes: "Added make_new_job.sh script and templates directory; updated instructions to reference templates instead of inline examples"
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changes: "Removed implementation_summary and learning_summary outputs; simplified step outputs"
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- version: "0.5.0"
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changes: "Standardized on 'ask structured questions' phrasing for user input; Updated quality criteria hooks to verify phrase usage; Added guidance in implement.md to use phrase in generated instructions"
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steps:
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Verify the job.yml output meets ALL quality criteria before completing:
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1. **User Understanding**: Did you fully understand the user's workflow by asking structured questions?
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2. **Structured Questions Used**: Did you ask structured questions (using the AskUserQuestion tool) to gather user input?
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3. **Clear Inputs/Outputs**: Does every step have clearly defined inputs and outputs?
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4. **Logical Dependencies**: Do step dependencies make sense and avoid circular references?
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5. **Concise Summary**: Is the summary under 200 characters and descriptive?
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6. **Rich Description**: Does the description provide enough context for future refinement?
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7. **Valid Schema**: Does the job.yml follow the required schema (name, version, summary, steps)?
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8. **File Created**: Has the job.yml file been created in `.deepwork/jobs/[job_name]/job.yml`?
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1. **User Understanding**: Did you fully understand the user's workflow through interactive Q&A?
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2. **Clear Inputs/Outputs**: Does every step have clearly defined inputs and outputs?
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3. **Logical Dependencies**: Do step dependencies make sense and avoid circular references?
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4. **Concise Summary**: Is the summary under 200 characters and descriptive?
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5. **Rich Description**: Does the description provide enough context for future refinement?
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6. **Valid Schema**: Does the job.yml follow the required schema (name, version, summary, steps)?
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7. **File Created**: Has the job.yml file been created in `.deepwork/jobs/[job_name]/job.yml`?
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If ANY criterion is not met, continue working to address it.
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If ALL criteria are satisfied, include `<promise>✓ Quality Criteria Met</promise>` in your response.
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3. **Specific & Actionable**: Are instructions tailored to each step's purpose, not generic?
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4. **Output Examples**: Does each instruction file show what good output looks like?
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5. **Quality Criteria**: Does each instruction file define quality criteria for its outputs?
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6. **Ask Structured Questions**: Do step instructions that gather user input explicitly use the phrase "ask structured questions"?
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7. **Sync Complete**: Has `deepwork sync` been run successfully?
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8. **Commands Available**: Are the slash-commands generated in `.claude/commands/`?
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9. **Policies Considered**: Have you thought about whether policies would benefit this job?
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6. **Sync Complete**: Has `deepwork sync` been run successfully?
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7. **Commands Available**: Are the slash-commands generated in `.claude/commands/`?
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8. **Policies Considered**: Have you thought about whether policies would benefit this job?
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- If relevant policies were identified, did you explain them and offer to run `/deepwork_policy.define`?
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- Not every job needs policies - only suggest when genuinely helpful.
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