Work Summary
by FuZhiyu
Create factual working journal entries in Notes/WorkingJournal/ after completing analysis work. Use when user asks to "summarize work", "document results", or "create working journal entry". Ensures code is committed, copies figures to attachments, and creates objective summaries with citations.
Skill Details
Repository Files
1 file in this skill directory
name: work-summary description: Create factual working journal entries in Notes/WorkingJournal/ after completing analysis work. Use when user asks to "summarize work", "document results", or "create working journal entry". Ensures code is committed, copies figures to attachments, and creates objective summaries with citations.
Work Summary Skill
Create factual working journal entries that document completed analysis work without interpretation or recommendations.
When to Use
Activate when user requests:
- "Summarize the work"
- "Document the results"
- "Create a working journal entry"
- "Write up the analysis"
Instructions
Step 1: Verify Git Commit
Check if code has been committed:
git status
If uncommitted changes exist:
- Inform user: "I see uncommitted changes. Should I run the code-quality-reviewer agent and commit the code first?"
- Wait for user confirmation
- If confirmed, use Task tool with
subagent_type="code-quality-reviewer"then assist with git commit - Get commit info:
git log -1 --pretty=format:"%H%n%s"
If clean: Get latest commit: git log -1 --pretty=format:"%H%n%s"
Step 2: Confirm Understanding
If you have context from recent work:
- Summarize your understanding of objective, code location, output location
- Use AskUserQuestion tool to confirm with user
If you don't have context:
- Ask user for: objective, code location, output location
Then read code files, output files, and documentation to gather information.
Step 3: Handle Figures
If figures exist in output folder:
mkdir -p Notes/WorkingJournal/attachments
cp Output/[subfolder]/figure.png Notes/WorkingJournal/attachments/YYYY-MM-DD-description.png
In markdown:

Source: [Original](../../Output/[subfolder]/figure.png)
Step 4: Create Working Journal Entry
Filename: Notes/WorkingJournal/YYYY-MM-DD-[Author]-[Description].md
Front Matter:
---
author: "[[Author]]"
date: YYYY-MM-DD
project: "[[IntermediaryDemand]]"
git_commit: [full hash if available]
git_message: "[message if available]"
permalink: working-journal/YYYY-MM-DD-author-description
---
Step 5: Write Summary
Structure can be flexible, but typically include:
- Objective section
- Summary of what was done
- Data description
- Methodology description
- Results with tables/figures
- Technical implementation details (code and outputs)
Use relative paths from Notes/WorkingJournal/:
- Code:
../../Code/ - Output:
../../Output/ - Data:
../../Data/
Critical Rules - MUST FOLLOW
1. Be Factual and Objective
✓ DO:
- State what was done and what was found
- Report numerical results precisely
- Describe methods used
- Link every claim to source (code, output, documentation)
✗ DO NOT:
- Interpret economic meaning without user request
- Speculate on causes or implications
- Make recommendations or suggest next steps
- Use subjective assessments ("excellent", "poor", "successful")
2. Examples
Good (Factual):
- "Processed 4.7M holdings from 11,857 submissions"
- "Difference of -30% (-$243B)"
- "Front-end tenors within 7% of benchmark"
- "Classification success rate: 70% (3,988 of 5,699)"
Bad (Speculative/Interpretive):
- "This suggests the classification is insufficient"
- "The results indicate strong performance"
- "This likely means we should use BKMS data"
- "The excellent match validates our approach"
3. Cite Everything
Every claim must link to supporting evidence:
[descriptive text](../../path/to/file)- Code files for methodology
- Output files for results
- Documentation for data sources
4. Figures
- Copy to attachments/ with descriptive filename
- Cite original source location
- Use descriptive captions
Step 6: Verify Report Quality
After creating the report, use the report-checker agent to verify quality:
Use Task tool with subagent_type="report-checker"
Pass: report path, code location, output location, objective
The agent will check:
- All claims are cited and accurate
- No speculation or unsupported interpretation
- Numbers match source files
- No subjective language
If issues found, revise the report before finalizing.
After Creating
- Tell user the file path
- List what was documented
- Report any issues found by report-checker
- Ask: "Would you like me to add any specific information?"
- Do NOT suggest interpretations or next steps unless asked
Related Skills
Dbt Transformation Patterns
Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.
Clinical Decision Support
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug develo
Scientific Schematics
Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.
Mermaid Diagrams
Comprehensive guide for creating software diagrams using Mermaid syntax. Use when users need to create, visualize, or document software through diagrams including class diagrams (domain modeling, object-oriented design), sequence diagrams (application flows, API interactions, code execution), flowcharts (processes, algorithms, user journeys), entity relationship diagrams (database schemas), C4 architecture diagrams (system context, containers, components), state diagrams, git graphs, pie charts,
Diagram Generation
Mermaid diagram generation for architecture visualization, data flow diagrams, and component relationships. Use for documentation, PR descriptions, and architectural analysis.
Matlab
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter
Dask
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
Scientific Schematics
Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.
Clinical Decision Support
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug develo
Materialize Docs
Materialize documentation for SQL syntax, data ingestion, concepts, and best practices. Use when users ask about Materialize queries, sources, sinks, views, or clusters.
