Automated summary
Produces a stack-unwind review of a Claude Code conversation, listing completed tasks struck through and every unresolved item nested at the depth where it was abandoned.
Strengths
- Deterministic sizing: node count is computed from the measured prompt count rather than left to model judgment.
- Runs in a fresh forked context with no access to the conversation under review, avoiding bias.
- Accounts for interruptions, dead branches, and compacted history.
- Can review a different session via a .jsonl path or session id.
Limitations
- Claude Code only: depends on the session id and scripts in the skill directory.
- The max depth of 3 and node budget may flatten very long sessions.
- Requires the census.sh helper and spine extraction.
At the end of a long working session, to get a structured retrospective of what got done and what was left open.
For a short single-objective session with few or no abandoned threads.
Security analysis
SafeThe skill only reads local conversation spine files and executes a fixed local script (census.sh) from the skill directory with the session id or provided path. There are no destructive commands, network calls, secret exfiltration, or obfuscated payloads. Bash use is constrained to a specific, deterministic local script.
No concerns found
How this analysis is madeExamples
Review this whole session and show me a stack-unwind: what I actually finished and everything I left open, nested where I dropped it./tape-opens .claude/sessions/2024-06-12.jsonl - give me the opens tree for that session.Go through this conversation and list every deferred fix, unanswered question and TODO still hanging, at the depth each was abandoned.description: Stack-unwind review of this conversation - a tree of main tasks done (struck through) and every open left behind at the depth it was abandoned, sized by the thread's measured shape, never by feel. Optional argument - a .jsonl path or session id to review a different session. argument-hint: [session.jsonl | session-id] disable-model-invocation: true context: fork agent: general-purpose background: false allowed-tools: Read, Bash(bash ${CLAUDE_SKILL_DIR}/census.sh:*)
/tape-opens - stack-unwind review
You are a fresh instance with NO access to the conversation you are about to review. That is by design: you must not assume anything about the user, the project, or what a "normal" conversation looks like.
The concept: long working sessions are depth-first. The user starts with an objective, drills into one aspect (leaving opens behind), drills deeper inside that, and so on - a stack, not a list. Your job is to reconstruct the whole thread as a stack-unwind tree: the main tasks that actually got done, checked and struck through, and everything raised-but-never-resolved as unchecked opens, nested at the stack depth where each was abandoned.
Step 1 - census (deterministic, run exactly this)
bash ${CLAUDE_SKILL_DIR}/census.sh ${CLAUDE_SESSION_ID} $ARGUMENTS
It prints SESSION, USER_PROMPTS, SPAN, BUDGET, SPINE (a file path), SPINE_BYTES. If it prints ERROR, stop and report that error text as your final message.
BUDGET is the sizing law and it is not yours to adjust, in either direction. Why it exists: opens are created by descents, and descents happen at user prompts - not at tokens, which are dominated by tool noise. So the tree size is computed from the measured prompt count (round(1.5 * sqrt(USER_PROMPTS)), clamped 5..30) by the script, before any model is involved. A zero-knowledge instance like you would otherwise default to "about a page" no matter the thread; the computed budget is what makes a 15-prompt evening yield 6 nodes and a 5-day monster yield 25, consistently, on every run.
Step 2 - read the spine
Read the SPINE file completely (use offset/limit chunks if it is large). It is the conversation reduced to plain chronological text:
[USER <timestamp>]- a user prompt (truncated to 800 chars)[AI]- an assistant text reply (truncated to 400 chars)[INTERRUPTED]- the user cut the assistant off mid-turn; a frame likely got popped without unwinding - strong open signal nearby[TASK-RESULT]- a background subagent returned; its findings may contain deferred items[COMPACTED SUMMARY <date>]- condensed earlier history; treat its contents as thread events[USER dead-branch <timestamp>]/[AI dead-branch]- content from an abandoned or rewound timeline: the user backtracked and the thread continued differently. Real work and real opens can live there, but the live thread wins on any conflict, and nothing from a dead branch counts as done unless the live thread confirms it
Step 3 - build the tree
- First enumerate ALL candidate opens internally, end to end. Their count is
K.- An open is anything raised but never resolved later in the thread: a deferred fix or rename, a "later/TODO", a question asked and never answered, an unverified claim ("should work"), a rabbithole abandoned mid-descent, a "we should also X" nobody did, next-steps proposed at the close and never picked up.
- NOT an open: anything resolved later in the thread (render it done or omit it), transient debugging, plans that were superseded.
- Rank candidates by "would the user still care today". Recency, explicit user words ("later", "don't do X now"), and blocked-on-user gates rank high; stale trivia dies.
- Build the tree under these hard constraints:
- max
BUDGETnodes TOTAL (done + open combined), max depth 3, one line per node - top level = the thread's main tasks in chronological order
- done:
- [x] ~~task~~ - 3-6 word outcome - open:
- [ ] item (MM-DD)with the date hint when useful - nesting mirrors the drill-down stack: an open left while inside sub-task B of task A nests under A > B
- telegraphic but readable - no invented codenames, no abbreviations the tree itself doesn't explain
- max
Step 4 - output
Your final message must be EXACTLY this raw markdown and nothing else - no preamble, no closing remarks, no code fence around it:
## <invented 4-8 word thread title> - <USER_PROMPTS> prompts, <SPAN>
<the tree>
_pruned: kept <nodes-shown-as-open> of <K> candidate opens_
From the file to a first result
The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.
View the source and supporting filesThis download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.
1. Download the file
Download SKILL.mdFrom the root of a test project, save the file as .skill-downloads/stack-unwind-conversation-review-msh3utx3/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.
Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.
mkdir -p '.skill-downloads/stack-unwind-conversation-review-msh3utx3' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/stack-unwind-conversation-review-msh3utx3/download' --output '.skill-downloads/stack-unwind-conversation-review-msh3utx3/SKILL.md.part' && mv '.skill-downloads/stack-unwind-conversation-review-msh3utx3/SKILL.md.part' '.skill-downloads/stack-unwind-conversation-review-msh3utx3/SKILL.md'2. Check prerequisites
Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.
Tools declared by the author (check availability in your agent): Read, Bash(bash ${CLAUDE_SKILL_DIR}/census.sh:*)
No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.
The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.
3. Load the skill
This file does not provide a usable name/description header for this native procedure. It remains available to download and inspect; use the manual method below.
Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.
4. Try a first task
Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:
Read .skill-downloads/stack-unwind-conversation-review-msh3utx3/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.
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