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/abilityai/cornelius/auto-discoverygit clone --depth 1 https://github.com/Abilityai/corneliusWhat 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 | $0.00022 | $0.04728 |
| Opus 5 | $0.00011 | $0.02364 |
| Sonnet 5 | $0.00004 | $0.00946 |
| Haiku 4.5 | $0.00002 | $0.00473 |
Grade A, and why
auto-discovery 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 2d 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 — 547 lines — stays where its author put it; the contents beside it link to each section on GitHub.
State Dependencies
| Source | Location | Read | Write | Description |
|---|---|---|---|---|
| Permanent Notes | Brain/02-Permanent/ |
✓ | Random sampling across clusters | |
| AI Extracted Notes | Brain/AI Extracted Notes/ |
✓ | Include in sampling | |
| Document Insights | Brain/Document Insights/ |
✓ | Include in sampling | |
| Local Brain Search | resources/local-brain-search/ |
✓ | Semantic search, hubs, bridges, stats | |
| Session Changelogs | Brain/05-Meta/Changelogs/ |
✓ | Dated auto-discovery changelog | |
| Master Changelog | Brain/CHANGELOG.md |
✓ | ✓ | Brief summary entry |
Local Brain Search
Use Local Brain Search for all semantic search operations.
Location: resources/local-brain-search/
Wrapper Scripts:
# Semantic search
resources/local-brain-search/run_search.sh "query" --limit 10 --json
# Find connections
resources/local-brain-search/run_connections.sh "Note Name" --json
# Find hub notes
resources/local-brain-search/run_connections.sh --hubs --json
# Get graph stats
resources/local-brain-search/run_connections.sh --stats --json
# Find bridges
resources/local-brain-search/run_connections.sh --bridges --json
READ SCOPE (load-bearing for this agent): cross-domain sampling across non-core
material (Document Insights, 05-Meta, etc.) IS this agent's purpose. With scope
enforcement on, a bare run_search.sh / run_connections.sh reads only the core
fingerprint and would silently sample nothing outside it - defeating the agent. So
prefix every search/connection command here with a wide read-scope, and pass
--no-track (autonomous sampling must not train q-values):
BRAIN_READ_SCOPE=core,Books,document-insights,meta,inbox,output resources/local-brain-search/run_search.sh "query" --limit 10 --no-track --json
BRAIN_READ_SCOPE=core,Books,document-insights,meta,inbox,output resources/local-brain-search/run_connections.sh "Note Name" --no-track --json
(--hubs/--bridges remain the core fingerprint by design - do not widen those.)
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.
- 2d ago First seen · 547 lines · 22 tokens per session scan A 9d9aaf4ac740
auto-discovery is an agent published in the GitHub repository Abilityai/cornelius (104 stars, last pushed 9d ago), licensed MIT. It adds 22 tokens to every session and 4,728 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 2026-08-30.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.