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/jonny-1812/corebee-mcp-skillsWrote 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/jonny-1812/corebee-mcp-skills/kb-status)<a href="https://agentmods.dev/commands/jonny-1812/corebee-mcp-skills/kb-status"><img src="https://agentmods.dev/badge/commands/jonny-1812/corebee-mcp-skills/kb-status/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/commands/jonny-1812/corebee-mcp-skills/kb-status"><img src="https://agentmods.dev/badge/commands/jonny-1812/corebee-mcp-skills/kb-status.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 | $0.00034 | $0.00325 |
| Opus 5 | $0.00017 | $0.00162 |
| Sonnet 5 | $0.00007 | $0.00065 |
| Haiku 4.5 | $0.00003 | $0.00032 |
Grade A, and why
kb-status 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.
What it actually says
/corebee:kb-status — Knowledge Base Health Check
Audit the AI knowledge base for completeness and errors.
Steps
- Call
list_knowledge_sourcesto get all sources - Count sources by status: active, pending, errored
- Flag any sources with 0 indexed chunks (empty)
- Flag any sources in error state
Output Format
Knowledge Base Health
- Total sources: [count]
- Active (indexed): [count]
- Pending: [count]
- Errored: [count]
| Source | Type | Status | Chunks | Last Updated |
|---|---|---|---|---|
| [name] | [url/file] | [status] | [count] | [date] |
Issues Found
- [source name]: Error — [error message]
- [source name]: Empty — 0 chunks indexed, may need re-crawl
Recommendations
- Suggest adding sources for common unanswered questions
- Suggest re-indexing errored sources
Rules
- Show source names, not IDs
- Display error messages for failed sources
- If everything is healthy, say so clearly
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 · 43 lines · 34 tokens per session scan A e3de094d17b1
kb-status is a command published in the GitHub repository jonny-1812/corebee-mcp-skills (0 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 325 once invoked, about $0.0002 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 commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
memory-store
Store an insight, decision, or pattern to memory.
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.
lians-recall
Recall current (non-stale) facts from Lians memory, optionally as-of a past date.