Session to Post

Capture what happened in a Claude Code session and turn it into a blog post, case study, or social media thread that others can learn from.

The skill extracts the real story from git history, file changes, and conversation context, then shapes it into a narrative that shows process, not just results.

When To Use

• After completing a meaningful chunk of work you want to share
• Creating dev blog content from real sessions
• Building case studies for tools, libraries, or techniques
• Producing marketing content that demonstrates capability
• Documenting a process for teammates who weren't in the session
• Sharing a session story with a Reddit community (r/programming, r/rust, r/Python, r/ClaudeAI, etc.)

When NOT To Use

• Writing API reference documentation (use scribe:doc-generator)
• Creating step-by-step tutorials (use scribe:tech-tutorial)
• Cleaning up existing prose (use scribe:slop-detector)
• Internal project documentation (use sanctum:doc-updates)

Integration Points

This skill connects to several others in the ecosystem. Use them when the post needs more than prose.

Need	Skill	What it adds
Terminal demo GIF	scry:vhs-recording	Record a build/test run as an animated GIF
Browser demo GIF	scry:browser-recording	Capture a web UI walkthrough via Playwright
Composite media	scry:media-composition	Stitch terminal and browser GIFs side-by-side
Proof of claims	imbue:proof-of-work	Verify every number in the post with evidence
Code quality narrative	pensive:code-refinement	Describe what was cleaned up and why
Review narrative	imbue:structured-review	Capture review findings as post content
Change summary	imbue:catchup	Summarize what changed for the post's "The Work" section
Diff analysis	imbue:diff-analysis	Risk-scored change breakdown for technical audiences

Recording Integration (scry)

When the post describes something visual (a running app, a test suite, a build pipeline) capture it instead of describing it.

Terminal recordings (build output, test runs, CLI demos):

Invoke Skill(scry:vhs-recording) with a tape that runs:
  make test        → shows 180 tests passing
  make play        → shows the build + server startup

Browser recordings (web apps, rendered output):

Invoke Skill(scry:browser-recording) with a Playwright spec that:
  navigates to the app
  interacts with it
  captures the result

Composition (side-by-side before/after, terminal and browser):

Invoke Skill(scry:media-composition) to stitch recordings into
a single visual that tells the story.

Place generated GIFs in docs/posts/assets/ and reference them from the markdown with relative paths.

Proof-of-Work Integration (imbue)

Every claim in the post should be verifiable. Before finalizing:

Invoke Skill(imbue:proof-of-work) to:
  - Tag each claim with [E1], [E2], etc.
  - Run verification commands
  - Report PASS / FAIL / BLOCKED

This prevents publishing posts with stale numbers or broken examples.

Methodology

Step 1: Extract Session Context

Load the session-extraction module for the full checklist.

Gather raw material from what actually happened:

1. Git history: commits since the session started:

   git log --oneline --since="<session_start>" --stat
   

2. File inventory: what was created and changed:

   git diff --stat <start_commit>..HEAD
   

3. Test results: concrete evidence of what works:

   cargo test  # or the project's test command
   

4. Metrics: scope and scale:

   find . -name "*.rs" -not -path "*/target/*" | xargs wc -l
   

5. Conversation context: the user's goals, constraints, and decisions made during the session

Step 2: Identify the Story

Every session post answers three questions:

1. What were we trying to do?: the goal, not the task list
2. What did we actually do?: the real path, including pivots
3. What came out of it?: concrete, measurable results

Look for:

• The hook: what makes this interesting? A hard problem, a surprising approach, an impressive result
• Turning points: where did the plan change? What broke? What worked unexpectedly?
• The number: one metric that captures the outcome (lines written, tests passing, performance gain, time saved)

Step 3: Draft the Post

Choose format first:

Format	Module	When
Blog post	narrative-structure	Dev blog, company blog, personal site
Case study	narrative-structure	Marketing, tool demonstrations
Social thread	narrative-structure	Twitter/X, Bluesky, LinkedIn
Reddit post	reddit-format	Community engagement, r/programming etc.

For Reddit: load modules/reddit-format.md instead of the blog template below. The structure, tone, and quality gate differ.

Load the narrative-structure module for blog/case-study templates.

Blog post structure (adapt to content):

# Title: [Verb] + [What] + [With What]

## Opening (2-3 sentences)
What we set out to do and why. No throat-clearing.

## Starting Point
Where things stood before. Concrete: file counts, code state,
what worked and what didn't.

## The Work
Key phases. Focus on decisions and pivots, not keystrokes.
- Phase 1: [what and why]
- Phase 2: [what and why]
Include GIFs from scry recordings where visual.

## How We Tested It
What verification looked like. Show the test run, the proof-of-work
evidence. Include terminal recording GIF of tests passing.

## Results
Hard numbers. Before/after. What works now.
Screenshots or browser recording GIF if visual.

## What's Next
Honest remaining work. No false completeness.

Tone:

• Write like explaining to a colleague over coffee
• Specifics over adjectives ("180 tests" not "comprehensive suite")
• Show the mess: readers connect with pivots and debugging
• Credit the tools and techniques that made it work
• Under 1500 words unless the content demands more

Step 4: Quality Gate

For blog posts and case studies:

1. Slop check: Skill(scribe:slop-detector) on the draft
2. Proof-of-work: Skill(imbue:proof-of-work) on all claims
3. Recording check: does any section need a GIF?
4. Title test: would you click this? Does it promise something specific?
5. Opening test: does paragraph one say what the post is about?

For Reddit posts (additional gates):

1. TL;DR present: is it after --- at the end?
2. Lede not buried: is the most interesting thing in the first two sentences?
3. Subreddit fit: does the content match the target subreddit's norms? Check the subreddit's top posts of the month.
4. First comment drafted: are the repo link and any reference material ready to post as a follow-up comment?
5. Header count: if the post is under 600 words, are headers absent (or replaced with bold inline labels)?

Step 5: Output

Write the post to the requested location (default: docs/posts/).

Report:

• Format used (blog post / case study / Reddit post)
• Word count
• Slop score (blog/case-study only)
• Verifiable claims count
• Recordings generated (if any)
• For Reddit: target subreddit and first-comment content

Example

A session that ported a Quake 2 engine from C to Rust:

Title: Rewriting a Quake 2 Engine in Rust with Claude Code

Opening: We took a 150,000-line C game engine and started rewriting it in Rust targeting WebAssembly. In one session we went from an empty workspace to a prototype loading real game data in the browser.

Starting point: A Yamagi Quake II fork compiled with Emscripten. Goal: idiomatic Rust with wasm-bindgen, glow for WebGL2, and matchbox for P2P multiplayer.

The work: Seven parallel agents built subsystems (collision, movement, filesystem, networking, renderer, server, client) while the main session coordinated integration. A Makefile with prerequisite checks automated the full build-to-browser pipeline including game data download.

How we tested: 180 unit tests across 13 crates. BSP loading verified against real Quake 2 demo pak0.pak. Browser diagnostics logged every init step. [Terminal GIF: make test output]

Results: 10,950 lines of Rust, 180 tests, real game data loading and flat-shaded BSP rendering in the browser with WASD movement and mouse look.

What's next: Textured rendering, collision debugging, sound, menus, multiplayer.

Every claim is checkable: line counts from wc -l, test counts from cargo test, file counts from filesystem log output.

Exit Criteria

• Format selected (blog post, case study, or Reddit post)
• Session brief compiled from git history and conversation context
• Draft written to docs/posts/ (or specified path)
• For blog/case-study: slop score reported, all claims tagged with evidence references
• For Reddit: TL;DR present, lede in first two sentences, target subreddit identified, first comment drafted
• Word count and verifiable claim count reported
• Incomplete or unverifiable claims are flagged, not silently dropped