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.
npx agentmods add commands/datacore-one/datacore/todaygit clone --depth 1 https://github.com/datacore-one/datacoreWrote 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/today)<a href="https://agentmods.dev/commands/datacore-one/datacore/today"><img src="https://agentmods.dev/badge/commands/datacore-one/datacore/today.svg" alt="Measured on agentmods" 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 | $0.00018 | $0.06261 |
| Opus 5 | $0.00009 | $0.03130 |
| Sonnet 5 | $0.00004 | $0.01252 |
| Haiku 4.5 | $0.00002 | $0.00626 |
Grade A, and why
today 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 today.
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 — 721 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Today
Your AI Chief of Staff's morning briefing. The main product deliverable of Data.
Command Context
Philosophy
This is not a dashboard. It is a personal briefing from someone who knows you — your energy, your patterns, your priorities, your life. The tone is a trusted chief of staff who also coaches: direct, warm, occasionally challenging.
The briefing tells a story in three acts:
- The World — what happened while you slept (news, markets, overnight work)
- Your Day — what needs you today (agenda, email, GitHub, decisions)
- Your Horizon — what is coming and what matters (week ahead, strategic view)
Design Principles
- Personalization over information — know the user, don't just report data
- Coach, don't report — gentle nudges, not bullet lists. "Your body says moderate today" not "Readiness: 72"
- Module slots, not hardcoded sections — modules fill slots in the narrative flow
- News first — set world context before personal agenda
- Done-first — show what Data accomplished overnight before asking for decisions
- Capacity-aware — every recommendation adjusted to Oura readiness
- Future-extensible — family, personal finance, health goals will plug in naturally
Quick Reference
| Question | Answer |
|---|---|
| Output location? | Personal space journal: 0-personal/notes/journals/YYYY-MM-DD.md |
| Nightshift outputs? | */0-inbox/nightshift-*.md |
| Calendar source? | Google Calendar — multiple accounts (from settings.local.yaml) |
| Market phase? | Pre-computed by nightshift cron at 05:30 UTC |
| What DIPs govern this? | DIP-0009 (GTD), DIP-0011 (Nightshift) |
Cron Schedule (nightshift server, UTC)
| Time | CEST | Job |
|---|---|---|
| 05:30 | 07:30 | /analyze-market-phase — trading signals for briefing |
| 06:00 | 08:00 | /today — morning briefing generation |
Step 1: Create Tracked Checklist
Before doing anything else, create a tracked task list for each step.
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.
- today First seen · 721 lines · 18 tokens per session scan A 335a70d348b2
today is a command published in the GitHub repository datacore-one/datacore (4 stars, last pushed today), licensed MIT. It adds 18 tokens to every session and 6,261 once invoked, about $0.0001 per session on Opus 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.
Other commands, from other repositories
prd-archive
Archive the active PRD (blocked until every accepted finding has a receipt).
prd-map
Build a codebase map so PRDs are written with repo context, not blind.
prd-split
Split the approved PRD into one issue spec per manifest entry.
rca-check
Lint an RCA or premortem document against the canonical template.
prd-approve
Advance the active PRD to approved (blocked by pending findings).
compress
Save this Claude Code session to the vault and update the semantic memory index.