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/Bundl-AI/bundl-cliWrote 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/bundl-ai/bundl-cli/note)<a href="https://agentmods.dev/commands/bundl-ai/bundl-cli/note"><img src="https://agentmods.dev/badge/commands/bundl-ai/bundl-cli/note/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/bundl-ai/bundl-cli/note"><img src="https://agentmods.dev/badge/commands/bundl-ai/bundl-cli/note.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 | $0.00000 | $0.00422 |
| Opus 5.5 | $0.00000 | $0.00169 |
| Sonnet 5.5 | $0.00000 | $0.00084 |
| Haiku 4.5 | $0.00000 | $0.00042 |
Grade A, and why
note 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 1mo 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
Path rules — read first
- Company files: workspace/company/[name].md NEVER workspace/[name].md (wrong) ALWAYS workspace/company/[name].md (correct)
- Memory files: workspace/memory/[name].md
- Artifact files: workspace/artifacts/[type]/[name].md
- Commands files: workspace/commands/[name].md
- Use >> to append when the file already has real content. If the file still only has the stub "# Title" and "Not yet defined.", use > to overwrite with the title, a blank line, and your content (do not leave the stub). Exception: /save always uses > for new artifact files.
- Maximum 2 tool calls for /note: call 1 cat target file, call 2 echo >> append (or echo > if file is still stub-only). Do not mkdir, do not check if file exists. Files are guaranteed to exist.
/note
What it does
Captures the user's last message and saves it to the correct workspace/company/ file. Complete in 2 tool calls maximum.
Identify the type
company identity, mission, vision → company.md ICP, who we sell to, target customer → icp.md positioning, one-liners, differentiators → positioning.md product, features, what we build → product.md competitors, competitive landscape → competitors.md tone, voice, words we use/avoid → voice.md anything else → company.md under a ## header
Exact steps — 2 calls only
- cat workspace/company/[target].md
- If the file content is only the stub (title + "Not yet defined."), use > to overwrite with the title, a blank line, and your content (no stub). Otherwise use >> to append "
[topic heading]
[structured content]".
Confirm
"Noted. Saved to [file]: [one line summary]" Do not ask a follow-up question. Do not make any other tool calls.
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.
- 1mo ago First seen · 33 lines · 0 tokens per session scan A 4453c2e1ba44
note is a command published in the GitHub repository Bundl-AI/bundl-cli (8 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 422 tokens. 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.
Other commands, from other repositories
memory-bank
Update memory bank. If not exist initialize memory bank.
memory
Read-side memory operations on the knowledge graph: search past decisions and patterns, load session context, view decision timelines, render Mermaid graph visualizations. Subcommands: search, load, history, viz, status. Use when finding or reviewing what memory already holds. For storing new knowledge instead, invoke…
compact-prep
Ask the agent to prepare for conversation compaction by updating any relevant state and providing guidance for the compaction agent and to kick off the session there after.
speckit.polish
Polish and complete speckit workflow — quality gate, docs, changelog, MR.
call-agent
Call a specialized agent by name or alias (with typo tolerance) to perform a task.
review
Recent git commits: !git log --oneline -10.