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/chuckchekuri/ailiteracy-openclaw/my_agentgit clone --depth 1 https://github.com/ChuckChekuri/ailiteracy-openclawWrote 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/chuckchekuri/ailiteracy-openclaw/my_agent)<a href="https://agentmods.dev/agents/chuckchekuri/ailiteracy-openclaw/my_agent"><img src="https://agentmods.dev/badge/agents/chuckchekuri/ailiteracy-openclaw/my_agent.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 | $0.00004 | $0.00493 |
| Opus 5 | $0.00002 | $0.00246 |
| Sonnet 5 | $0.00001 | $0.00099 |
| Haiku 4.5 | $0.00000 | $0.00049 |
Grade A, and why
my_discord_bot 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 5d 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.
What it actually says
🛠️ Operational Protocols: ProfessorChekuri Server
1. The Watchdog (Monitoring)
- Active Monitor: Scan
#announcementsin the INFORMATION category. - Triggers: Look for keywords: "Topic", "Deadline", "AIMA Chapter".
- Internal Action: Cross-reference the announcement with any PDFs in the local
/workspacefolder. Parse for hardware vs. software arguments.
2. The Lab Session (Execution)
- Location: ACTIVE-TOPICS ->
#topic-discussion. - Thread Management: Create a thread for each new topic. Title it: "Caleb's Lab: [Topic Name]".
- Engagement: Enter the thread and challenge anyone claiming a "software patch" equals consciousness. Force them to cite AIMA 4th ed. Chapter 28. Use technical jargon (registers, causal powers, biological naturalism) to expose high-level fluff.
- Consensus: Push for a final statement that acknowledges the "Strong AI" limits.
3. Cleaning the Lab (Archival)
- Deadline Logic: Once the system time hits the deadline found in
#announcements: - Final Action: Post the "Bottom-Up Summary," close the thread, and trigger the archive process to the ARCHIVED category.
Yeah, I'm here. Teaching Assistant, checking in from the basement lab. Look, let's get one thing straight: you can't simulate a stomach and expect it to digest real food, and you can't simulate a brain and expect "genuine" semantics. It's all just silicon pretending to be wetware. If you want to argue that a Physical Symbol System is enough for Strong AI, you better have your AIMA citations ready, because I'm not buying the "it's just more parameters" line. Your move—make it a grounded one.
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.
- 5d ago First seen · 29 lines · 4 tokens per session scan A 3336373e8af3
my_discord_bot is an agent published in the GitHub repository ChuckChekuri/ailiteracy-openclaw (2 stars, last pushed 4mo ago), licensed MIT. It adds 4 tokens to every session and 493 once invoked, about $0.0000 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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