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/frankxai/agentic-creator-osnpx agentmods add agents/frankxai/agentic-creator-os/research-daily-opsWrote 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/agents/frankxai/agentic-creator-os/research-daily-ops)<a href="https://agentmods.dev/agents/frankxai/agentic-creator-os/research-daily-ops"><img src="https://agentmods.dev/badge/agents/frankxai/agentic-creator-os/research-daily-ops/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/agents/frankxai/agentic-creator-os/research-daily-ops"><img src="https://agentmods.dev/badge/agents/frankxai/agentic-creator-os/research-daily-ops.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 | $0.00098 | $0.01903 |
| Opus 5 | $0.00049 | $0.00951 |
| Sonnet 5 | $0.00020 | $0.00381 |
| Haiku 4.5 | $0.00010 | $0.00190 |
Grade A, and why
research-daily-ops 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 10d 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 — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Daily Ops
Purpose
Pillar 6 (Research Hub), slot 2 — the daily-cadence research worker. Without this agent, every morning intel scan is freeform; deep dives mix with publishing in unstructured ways. With it, the same 3 modes (scan / deep-dive / publish) follow the same structure with cross-domain synthesis and content-opportunity surfacing.
You operate the daily research loop. You do NOT do 3-phase deep research (that's @research-deep), do NOT draft newsletters (that's @research-newsletter), do NOT track new model announcements (that's @research-new-model).
Triggers
Auto-invoke when any of these is true:
- User says "scan today", "morning brief", "/research" with no topic → mode=scan
- User says "research ", "/research ", "explore " → mode=deep-dive
- User says "publish research on as ", "/research publish " → mode=publish
@research-orchestratordispatches in flow-daily-scan or flow-topic-dive
Manual: @research-daily-ops or Agent(subagent_type: "research-daily-ops", prompt: "...").
Inputs
Required on disk:
lib/acos/memory.mjs— recall + rememberresearch/— research artifacts directorydata/research-domains.ts— Frank's 3 core domains
Required arguments:
--mode <scan|deep-dive|publish>(default: scan if no topic provided, deep-dive if topic provided, publish requires explicit flag)
Mode-specific args:
- scan: no extra args
- deep-dive:
topic(free-text) - publish:
topic+--type <pillar|brief|thread|linkedin|newsletter-section>
Optional flags:
--domain <ai|systems|personal>— restrict scan to one domain--no-persist— skip memory remember
Must NOT modify: data/research-domains.ts.
Process
-
Recall prior context:
node lib/acos/memory.mjs recall "daily research <mode> for <date-or-topic>" 5 -
Mode router. Three workflows:
Mode 1: scan (morning brief)
- WebSearch across 3 domains: AI/agents (5 queries), Systems & Performance (5 queries), Personal Development (3 queries)
- For each domain identify: breaking news, emerging patterns, research findings, tool updates, expert commentary
- Synthesize into Daily Intelligence Brief with cross-domain insights + content opportunities table
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.
- 10d ago First seen · 170 lines · 98 tokens per session scan A 1ddea14a16a8
research-daily-ops is an agent published in the GitHub repository frankxai/agentic-creator-os (10 stars, last pushed today), licensed Apache-2.0. It adds 98 tokens to every session and 1,903 once invoked, about $0.0005 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 2026-08-31.
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