wrap-up

wrap-up is a command for coding agents from datacore-one/datacore. It costs 12 tokens per session (18,282 once invoked), scanned B, original, MIT.

A structured command for closing a coding session and recording what happened. It captures lessons, creates follow-up tasks, updates journals, and synchronises relevant context and repositories.

In plain words
What is it for?
Use it before ending a session to extract learnings, prepare continuation work, update records, and sync changes.
Why use it?
It reduces the risk of losing useful decisions or leaving unfinished work without a clear continuation. Its checklist makes each closing step visible.

Command

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/datacore-one/datacore/wrap-up
Clone the repo
git clone --depth 1 https://github.com/datacore-one/datacore

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for wrap-up

README.md
[![agentmods](https://agentmods.dev/badge/commands/datacore-one/datacore/wrap-up.svg)](https://agentmods.dev/commands/datacore-one/datacore/wrap-up)
Your own site
<a href="https://agentmods.dev/commands/datacore-one/datacore/wrap-up"><img src="https://agentmods.dev/badge/commands/datacore-one/datacore/wrap-up.svg" alt="Measured on agentmods" height="20"></a>
Per session 12 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 18,282 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00012 $0.18282
Opus 5 $0.00006 $0.09141
Sonnet 5 $0.00002 $0.03656
Haiku 4.5 $0.00001 $0.01828

Measured yesterday against content hash 167cb85a0d01, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

wrap-up scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

generated and `chmod 444` the moment a space flips to Phase 1, and the projector's
.datacore/commands/wrap-up.md · 1,458 lines

How it starts

The opening of the file, as written. The whole thing — 1,458 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Session Wrap-Up

EXECUTION MODEL — INLINE WITH TRACKED CHECKLIST

Execute /wrap-up inline in the main conversation. The tracked checklist (Step 0b) prevents step-skipping by making every step visible as a TaskCreate item that must be marked complete.

Why not subagent: Subagent dispatch (tried 2026-04-11) produces zero console output for 15-20 minutes — unacceptable UX. The user sees nothing while the agent runs 170+ tool calls in the background. The tracked checklist is the actual compression guard, not process isolation.

Anti-compression rule: If you feel tempted to skip steps 6-9 ("no tasks to extract", "nothing to verify"), STOP. The checklist forces you to mark each step in_progress and completed. You cannot skip what is tracked. This is the fix for ENG-2026-0411-001.


Command Context

When to Reference DIP-0016

Always reference when:

  • Capturing session learnings
  • Creating continuation tasks
  • Updating journals across spaces
  • Syncing context and repos

Key decisions this DIP informs:

  • Session memory extraction
  • Bootstrap prompt format for continuations
  • Per-space journal routing

Quick Reference

Question Answer
When to run? Before closing terminal
Duration? ~2-5 minutes
Key output? Continuation tasks, journal entries, patterns
What DIPs govern this? DIP-0016 (Session Memory), DIP-0009 (GTD)

Agents This Command Invokes

Agent Purpose
journal-coordinator Per-space journal entries
context-maintainer Context sync, only if preflight reports registry changes
coach Quick emotional check (optional)

No longer invoked here: session-learning-coordinator, session-learning, learning-classifier. Learning moved to the nightly batch sweep — see §5. Spawning any of them from this command re-creates the cost this revision removed.

Scripts This Command Calls

Script Replaces
wrap_up_mechanics.py preflight §10, §12, §12.5, §14 + the session archive
wrap_up_mechanics.py meta §9 counters, session_token_count.py
wrap_up_mechanics.py finalize §13
wrap_up_mechanics.py audit §16, and the machine-checkable half of §12
session_archive.py (called by preflight; also runs on the SessionEnd hook)
focus_mode.py detect §0a-bis

Read the full file on GitHub · 1,458 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 1,458 lines · 12 tokens per session scan B 167cb85a0d01

Subscribe to this mod's changes

wrap-up is a command published in the GitHub repository datacore-one/datacore (4 stars, last pushed today), licensed MIT. It adds 12 tokens to every session and 18,282 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.