assumption-logging
Capture and structure assumptions from pilot plans and hypotheses into a centralized log for ongoing risk monitoring and stakeholder alerts. Use when extracting, tracking, and signaling assumption changes from pilot documentation.
Best use case
assumption-logging is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Capture and structure assumptions from pilot plans and hypotheses into a centralized log for ongoing risk monitoring and stakeholder alerts. Use when extracting, tracking, and signaling assumption changes from pilot documentation.
Teams using assumption-logging should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/assumption-logging/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How assumption-logging Compares
| Feature / Agent | assumption-logging | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Capture and structure assumptions from pilot plans and hypotheses into a centralized log for ongoing risk monitoring and stakeholder alerts. Use when extracting, tracking, and signaling assumption changes from pilot documentation.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Assumption Logging ## Overview [TODO: 1-2 sentences explaining what this skill enables] ## Structuring This Skill [TODO: Choose the structure that best fits this skill's purpose. Common patterns: **1. Workflow-Based** (best for sequential processes) - Works well when there are clear step-by-step procedures - Example: DOCX skill with "Workflow Decision Tree" -> "Reading" -> "Creating" -> "Editing" - Structure: ## Overview -> ## Workflow Decision Tree -> ## Step 1 -> ## Step 2... **2. Task-Based** (best for tool collections) - Works well when the skill offers different operations/capabilities - Example: PDF skill with "Quick Start" -> "Merge PDFs" -> "Split PDFs" -> "Extract Text" - Structure: ## Overview -> ## Quick Start -> ## Task Category 1 -> ## Task Category 2... **3. Reference/Guidelines** (best for standards or specifications) - Works well for brand guidelines, coding standards, or requirements - Example: Brand styling with "Brand Guidelines" -> "Colors" -> "Typography" -> "Features" - Structure: ## Overview -> ## Guidelines -> ## Specifications -> ## Usage... **4. Capabilities-Based** (best for integrated systems) - Works well when the skill provides multiple interrelated features - Example: Product Management with "Core Capabilities" -> numbered capability list - Structure: ## Overview -> ## Core Capabilities -> ### 1. Feature -> ### 2. Feature... Patterns can be mixed and matched as needed. Most skills combine patterns (e.g., start with task-based, add workflow for complex operations). Delete this entire "Structuring This Skill" section when done - it's just guidance.] ## [TODO: Replace with the first main section based on chosen structure] [TODO: Add content here. See examples in existing skills: - Code samples for technical skills - Decision trees for complex workflows - Concrete examples with realistic user requests - References to scripts/templates/references as needed] ## Resources (optional) Create only the resource directories this skill actually needs. Delete this section if no resources are required. ### scripts/ Executable code (Python/Bash/etc.) that can be run directly to perform specific operations. **Examples from other skills:** - PDF skill: `fill_fillable_fields.py`, `extract_form_field_info.py` - utilities for PDF manipulation - DOCX skill: `document.py`, `utilities.py` - Python modules for document processing **Appropriate for:** Python scripts, shell scripts, or any executable code that performs automation, data processing, or specific operations. **Note:** Scripts may be executed without loading into context, but can still be read by Codex for patching or environment adjustments. ### references/ Documentation and reference material intended to be loaded into context to inform Codex's process and thinking. **Examples from other skills:** - Product management: `communication.md`, `context_building.md` - detailed workflow guides - BigQuery: API reference documentation and query examples - Finance: Schema documentation, company policies **Appropriate for:** In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Codex should reference while working. ### assets/ Files not intended to be loaded into context, but rather used within the output Codex produces. **Examples from other skills:** - Brand styling: PowerPoint template files (.pptx), logo files - Frontend builder: HTML/React boilerplate project directories - Typography: Font files (.ttf, .woff2) **Appropriate for:** Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output. --- **Not every skill requires all three types of resources.**
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