docs: Add blog post and new slash commands for development workflow

- Add blog post: 4 Essential Slash Commands I Use in Every Project
- Add new slash commands: /doc-refactor, /setup-ci-cd, /unit-test-expand
- Update slash-commands README with comprehensive documentation
- Simplify /push-all command structure
- Archive add-blog-post-slash-commands change
- Add blog-post spec and pending openspec changes

openspec/changes/add-context-tracking-hooks/specs/hooks-documentation/spec.md

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+# hooks-documentation Spec Delta
+
+## ADDED Requirements
+
+### Requirement: Pre-Message and Post-Response Hook Pairs Documentation
+The hooks lesson SHALL document how to use `UserPromptSubmit` and `Stop` hooks together for context/token usage tracking.
+
+#### Scenario: Understanding hook event timing for context tracking
+- **WHEN** a user wants to track per-request token consumption
+- **THEN** they find documentation explaining that `UserPromptSubmit` fires before the prompt is processed (pre-message)
+- **AND** they find documentation explaining that `Stop` fires after Claude completes its response (post-response)
+- **AND** they understand how to calculate the delta between these two points
+
+#### Scenario: Token delta calculation methodology
+- **WHEN** a user implements a context tracking hook pair
+- **THEN** they find documentation explaining how to:
+  - Record token count at `UserPromptSubmit` time
+  - Calculate new token count at `Stop` time
+  - Compute the delta representing per-request consumption
+
+### Requirement: Context Tracking Hook Pair Example
+The hooks lesson SHALL provide a working example script that tracks context usage using pre-message and post-response hooks.
+
+#### Scenario: Single script handles both hook events
+- **WHEN** a user copies the context-tracker.py example
+- **THEN** the script detects the hook event type via `hook_event_name`
+- **AND** handles `UserPromptSubmit` by saving current token estimate to a temp file
+- **AND** handles `Stop` by loading the saved count, calculating delta, and reporting usage
+
+#### Scenario: Complete configuration for hook pair
+- **WHEN** a user wants to configure both hooks
+- **THEN** they find a complete settings.json example showing:
+  - `UserPromptSubmit` hook configuration pointing to the context tracker script
+  - `Stop` hook configuration pointing to the same script
+  - Both hooks using the same script for consistent token calculation
+
+#### Scenario: Per-request usage reporting
+- **WHEN** the context tracking hooks execute
+- **THEN** the Stop hook outputs a report showing:
+  - Total estimated tokens used in session
+  - Tokens consumed by the current request (delta)
+  - Remaining capacity estimate
+
+### Requirement: Token Counting Methods Documentation
+The hooks lesson SHALL document two offline token counting methods that require no API key.
+
+#### Scenario: tiktoken-based token counting documented
+- **WHEN** a user wants more accurate offline token counts
+- **THEN** they find documentation for using `tiktoken` with `p50k_base` encoding
+- **AND** they see a Python example using `tiktoken.get_encoding("p50k_base")`
+- **AND** they understand it provides ~90-95% accuracy compared to Claude's tokenizer
+- **AND** they learn it requires the `tiktoken` dependency
+
+#### Scenario: Character estimation token counting documented
+- **WHEN** a user wants zero-dependency token estimation
+- **THEN** they find documentation for the ~4 characters per token estimation ratio
+- **AND** they understand this provides ~80-90% accuracy for English text
+- **AND** they learn it works with no external dependencies
+
+#### Scenario: Method comparison provided
+- **WHEN** a user needs to choose between token counting methods
+- **THEN** they find a comparison showing:
+  - tiktoken method: ~90-95% accuracy, requires tiktoken, <10ms latency
+  - Estimation method: ~80-90% accuracy, no dependencies, <1ms latency
+- **AND** both methods work completely offline without API keys
+
+#### Scenario: Transcript contents explained
+- **WHEN** a user wants to understand what's included in token counts
+- **THEN** they find documentation explaining that the transcript includes:
+  - User prompts
+  - Claude's responses
+  - Tool inputs and outputs
+- **AND** they understand that system prompts and internal context are NOT included
+
+#### Scenario: No official Claude tokenizer caveat
+- **WHEN** a user reads about token counting accuracy
+- **THEN** they understand that Anthropic hasn't released an official offline tokenizer
+- **AND** they understand both methods are approximations based on similar BPE tokenizers
+
+## MODIFIED Requirements
+
+### Requirement: Context Usage Reporting Hook Example
+The hooks lesson SHALL include a correct, working example showing how to create a hook that reports context/token usage after each Claude response.
+
+#### Scenario: Token calculation is correct
+- **WHEN** a user copies the context-usage.py example
+- **AND** runs it as a Stop hook
+- **THEN** the hook correctly calculates estimated tokens from total character count
+- **AND** displays a non-zero token count proportional to conversation length
+
+#### Scenario: User learns to create context monitoring hook
+- **WHEN** a user reads the context usage reporter example
+- **THEN** they find a complete Python script that reads the transcript file
+- **AND** they understand how to estimate token usage from conversation history
+- **AND** they see the configuration for Stop hooks
+- **AND** they understand the limitations of token estimation
+
+#### Scenario: Hook output format is documented
+- **WHEN** a user implements the context usage hook
+- **THEN** they can generate a one-line report showing used tokens and remaining capacity
+- **AND** the output shows realistic token counts based on conversation size
+
+#### Scenario: Delta-based tracking is documented
+- **WHEN** a user wants per-request token consumption
+- **THEN** they find documentation pointing to the pre-message/post-response hook pair approach
+- **AND** they understand how to use `UserPromptSubmit` + `Stop` for delta calculation