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 commands/vybe/project_cornelius/analyze-kbgit clone --depth 1 https://github.com/vybe/project_corneliusWrote 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/commands/vybe/project_cornelius/analyze-kb)<a href="https://agentmods.dev/commands/vybe/project_cornelius/analyze-kb"><img src="https://agentmods.dev/badge/commands/vybe/project_cornelius/analyze-kb.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 | $0.00012 | $0.00514 |
| Opus 5 | $0.00006 | $0.00257 |
| Sonnet 5 | $0.00002 | $0.00103 |
| Haiku 4.5 | $0.00001 | $0.00051 |
Grade A, and why
analyze-kb 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 4d 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
100% identical to analyze-kb — 0 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.
What it actually says
Analyze the Obsidian knowledge base structure and regenerate a condensed, manageable analysis report.
Follow these steps:
- Get vault statistics using
mcp__smart-connections__get_stats - List all notes with full directory tree using
Bashfind:find /path/to/your/vault -name "*.md" -type f | head -50 - Use
Globto explore directory structure:- All notes:
Brain/**/*.md - Permanent notes:
Brain/02-Permanent/*.md - MOCs:
Brain/03-MOCs/*.md - Sources:
Brain/01-Sources/**/*.md
- All notes:
- Read key hub notes from major clusters using
Readtool (Dopamine, Self/Buddhism, Decision-Making, Flow, etc.) - Use
mcp__smart-connections__get_similar_notesto identify highly connected notes - Use
mcp__smart-connections__get_connection_graphto map relationship networks - Analyze thematic clusters, hierarchical organization, and conceptual architecture
- Use
EditorWriteto update theknowledge-base-analysis.mdfile with a condensed report (target: ~600-800 lines max):- Executive summary with key statistics
- Hierarchical structure mapping (condensed)
- 6 major thematic hubs with hub nodes (core thesis + key notes only)
- Network properties and connectivity (metrics + critical bridges)
- Content topology and source analysis (top-tier influences only)
- Intellectual trajectory and maturity assessment (phases + current focus)
- Recommendations for enhancement (high priority only)
CRITICAL OUTPUT REQUIREMENTS:
- Length target: 600-800 lines maximum (50% of previous verbose reports)
- Prioritize: Core insights, actionable frameworks, critical statistics, key bridge notes
- Eliminate: Excessive examples, redundant explanations, verbose elaborations
- Focus: What's unique, what's actionable, what's growing, what's next
- Style: Bullet points over paragraphs, tables over lists where appropriate
- No duplication: Say things once, clearly, then move on
Generate a condensed, scannable, high-signal report that reveals the knowledge base's personality, cognitive fingerprint, and growth opportunities without overwhelming detail.
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.
- 4d ago First seen · 42 lines · 12 tokens per session scan A e647fc10250a
analyze-kb is a command published in the GitHub repository vybe/project_cornelius (5 stars, last pushed 10mo ago), licensed MIT. It adds 12 tokens to every session and 514 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to analyze-kb, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
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session-end
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memory-store
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cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.