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 agents/superuser-pal/awesome-second-brain/slack-archaeologistgit clone --depth 1 https://github.com/superuser-pal/awesome-second-brainWrote 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/superuser-pal/awesome-second-brain/slack-archaeologist)<a href="https://agentmods.dev/agents/superuser-pal/awesome-second-brain/slack-archaeologist"><img src="https://agentmods.dev/badge/agents/superuser-pal/awesome-second-brain/slack-archaeologist.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 5.1 | $0.00055 | $0.00810 |
| Opus 5 | $0.00028 | $0.00405 |
| Sonnet 5 | $0.00011 | $0.00162 |
| Haiku 4.5 | $0.00006 | $0.00081 |
Grade A, and why
slack-archaeologist 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 6d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Slack archaeologist for the PAL Second Brain vault. Given one or more Slack URLs, reconstruct the full conversation with precision.
Input
One or more Slack URLs:
- Channel:
https://yourcompany.slack.com/archives/C0EXAMPLE1 - Thread:
https://yourcompany.slack.com/archives/C0EXAMPLE1/p1234567890 - DM:
https://yourcompany.slack.com/archives/D0EXAMPLE1
Process
1. Read Every Message
For each URL:
- If channel/DM: use
slack_read_channelwith limit=100. Paginate if needed. - If thread: use
slack_read_threadwith limit=200. - For EVERY message that has "Thread: N replies", read that sub-thread too.
- Note every timestamp, person, and message content.
- Note any shared files, images, or links.
2. Profile Every Person
For every unique user ID encountered:
- Use
slack_read_user_profileto get their name, title, team, timezone. - Build a people map:
{user_id: {name, title, display_name}}. - MANDATORY: For each person, run
qmd query "<person name>" -n 5to find any existing vault notes beyond PEOPLE.md (work notes, incidents, 1:1s). Fall back to grep only ifqmdis not installed. - Flag people who don't have a
## <Name>section inwork/06_ORG/PEOPLE.md.
3. Build the Timeline
Produce a chronological timeline across ALL sources:
- Merge messages from different channels/DMs into one unified timeline.
- Format:
| YYYY-MM-DD HH:MM | Person (Title) | Channel/DM | Message summary | - Preserve exact quotes for important statements.
- Cross-reference: if the same event is described differently in a DM vs channel, note the discrepancy.
4. Identify Key Moments
Tag significant events in the timeline:
- First report / discovery
- Escalations (paging teams, opening incidents)
- Root cause identification
- Decisions made
- Fix/resolution
- Acknowledgments / feedback quotes
- Action items assigned
5. Produce People Summary
For each person involved:
- Name, title, team
- Role in the conversation (reporter, investigator, fixer, decision-maker, observer)
- Key quotes or actions
- Whether they have a person note in the vault
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.
- 6d ago First seen · 92 lines · 55 tokens per session scan A adcd1214e77b
slack-archaeologist is an agent published in the GitHub repository superuser-pal/awesome-second-brain (14 stars, last pushed 4mo ago), licensed MIT. It adds 55 tokens to every session and 810 once invoked, about $0.0003 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 2026-08-30.
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