Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/datacore-one/datacorenpx agentmods add commands/datacore-one/datacore/tomorrowWrote 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.
[](https://agentmods.dev/commands/datacore-one/datacore/tomorrow)<a href="https://agentmods.dev/commands/datacore-one/datacore/tomorrow"><img src="https://agentmods.dev/badge/commands/datacore-one/datacore/tomorrow/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/datacore-one/datacore/tomorrow"><img src="https://agentmods.dev/badge/commands/datacore-one/datacore/tomorrow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00016 | $0.06378 |
| Opus 5.5 | $0.00006 | $0.02551 |
| Sonnet 5.5 | $0.00003 | $0.01276 |
| Haiku 4.5 | $0.00002 | $0.00638 |
Grade A, and why
tomorrow scanned grade A with 0 findings 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 18d ago.
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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 788 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tomorrow
Command Context
When to Reference DIP-0011
Always reference when:
- Queuing tasks for nightshift execution
- Routing :AI: tagged tasks to nightshift.org
- Reviewing overnight execution pipeline
- Estimating execution time and cost
Key decisions this DIP informs:
- Task movement from next_actions.org → nightshift.org
- Queue optimization (impact/effort/urgency)
- Nightshift server triggering
Quick Reference
| Question | Answer |
|---|---|
| AI queue? | org/nightshift.org |
| When to run? | End of work day |
| Server trigger? | Push triggers server execution |
| What DIPs govern this? | DIP-0011 (Nightshift), DIP-0009 (GTD) |
Agents This Command Invokes
| Agent | Purpose |
|---|---|
session-learning-coordinator |
Pattern extraction |
coach |
Evening REBT reflection (optional) |
Integration Points
- DIP-0011 - Nightshift pipeline
- DIP-0009 - GTD daily end workflow
- /today - Morning counterpart
"End of watch. Securing all stations for the night."
End-of-day command that closes out today, celebrates accomplishments, and builds excitement for tomorrow. The counterpart to /today.
Purpose
- Celebrate what you accomplished today
- Process inbox to zero (or delegate)
- Delegate work to AI for overnight execution
- Ensure system is clean and synced
- Build excitement for tomorrow
Duration
~10 minutes (mostly automated, optional user input)
Behavior
Execute the evening shutdown sequence with a focus on accomplishment and anticipation.
Step 0: Create Tracked Checklist (MANDATORY FIRST STEP)
Before doing anything else, start the run's checklist with the Datacore step tracker. This prevents step skipping in end-of-day processing, and it works in every harness because the checklist lives in today's personal journal:
python3 .datacore/lib/command_steps.py resume tomorrow # an unfinished run from earlier? continue it
python3 .datacore/lib/command_steps.py start tomorrow # otherwise: one "- [ ]" per "### N." step below
python3 .datacore/lib/command_steps.py tick <run_id> 4b # the moment a step completes (--note "reason" if it did not run)
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.
- 18d ago Changed · +2 lines 0459c4c17b67
- 20d ago Changed · +15 lines 5c3261129db8
- 1mo ago Changed 7468c867bc58
- 1mo ago Changed · +1 lines da3b14a29e43
- 1mo ago First seen · 770 lines · 16 tokens per session scan A 49d2b679a19c
tomorrow is a command published in the GitHub repository datacore-one/datacore (4 stars, last pushed yesterday), licensed MIT. It adds 16 tokens to every session and 6,378 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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