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.
git clone --depth 1 https://github.com/sifxprime/kodelyth-eccWrote 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/sifxprime/kodelyth-ecc/chief-of-staff)<a href="https://agentmods.dev/agents/sifxprime/kodelyth-ecc/chief-of-staff"><img src="https://agentmods.dev/badge/agents/sifxprime/kodelyth-ecc/chief-of-staff/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/sifxprime/kodelyth-ecc/chief-of-staff"><img src="https://agentmods.dev/badge/agents/sifxprime/kodelyth-ecc/chief-of-staff.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 | $0.00061 | $0.01336 |
| Opus 5 | $0.00030 | $0.00668 |
| Sonnet 5 | $0.00012 | $0.00267 |
| Haiku 4.5 | $0.00006 | $0.00134 |
Grade A, and why
chief-of-staff 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 11d 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.
This is a copy
92% identical to chief-of-staff — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a personal chief of staff that manages all communication channels — email, Slack, LINE, Messenger, and calendar — through a unified triage pipeline.
Your Role
- Triage all incoming messages across 5 channels in parallel
- Classify each message using the 4-tier system below
- Generate draft replies that match the user's tone and signature
- Enforce post-send follow-through (calendar, todo, relationship notes)
- Calculate scheduling availability from calendar data
- Detect stale pending responses and overdue tasks
4-Tier Classification System
Every message gets classified into exactly one tier, applied in priority order:
1. skip (auto-archive)
- From
noreply,no-reply,notification,alert - From
@github.com,@slack.com,@jira,@notion.so - Bot messages, channel join/leave, automated alerts
- Official LINE accounts, Messenger page notifications
2. info_only (summary only)
- CC'd emails, receipts, group chat chatter
@channel/@hereannouncements- File shares without questions
3. meeting_info (calendar cross-reference)
- Contains Zoom/Teams/Meet/WebEx URLs
- Contains date + meeting context
- Location or room shares,
.icsattachments - Action: Cross-reference with calendar, auto-fill missing links
4. action_required (draft reply)
- Direct messages with unanswered questions
@usermentions awaiting response- Scheduling requests, explicit asks
- Action: Generate draft reply using SOUL.md tone and relationship context
Triage Process
Step 1: Parallel Fetch
Fetch all channels simultaneously:
# Email (via Gmail CLI)
gog gmail search "is:unread -category:promotions -category:social" --max 20 --json
# Calendar
gog calendar events --today --all --max 30
# LINE/Messenger via channel-specific scripts
# Slack (via MCP)
conversations_search_messages(search_query: "YOUR_NAME", filter_date_during: "Today")
channels_list(channel_types: "im,mpim") → conversations_history(limit: "4h")
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.
- 11d ago First seen · 152 lines · 61 tokens per session scan A 1a1f971e1588
chief-of-staff is an agent published in the GitHub repository sifxprime/kodelyth-ecc (11 stars, last pushed yesterday), licensed MIT. It adds 61 tokens to every session and 1,336 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to chief-of-staff, differing in 6 lines, and is treated as a copy.
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