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/jayvee/aigonWrote 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/jayvee/aigon/arr)<a href="https://agentmods.dev/commands/jayvee/aigon/arr"><img src="https://agentmods.dev/badge/commands/jayvee/aigon/arr/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/jayvee/aigon/arr"><img src="https://agentmods.dev/badge/commands/jayvee/aigon/arr.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 | $0.00017 | $0.00263 |
| Opus 5.5 | $0.00007 | $0.00105 |
| Sonnet 5.5 | $0.00003 | $0.00053 |
| Haiku 4.5 | $0.00002 | $0.00026 |
Grade A, and why
arr 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.
This is a copy
91% identical to research-reset — 2 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
aigon-research-reset
Reset a research topic back to a fresh backlog state.
aigon research-reset {{args}}
What this does
research-reset performs research-specific cleanup in one command:
- Closes active sessions for the research ID
- Removes findings logs (
research-<id>-*-findings.md) - Removes research status files in
.aigon/state/ - Removes matching heartbeat files for research agents
- Returns the lifecycle to backlog and refreshes the generated view
- Removes workflow engine state in
.aigon/workflows/research/<id>/
Reset is idempotent. Running it again after cleanup is a no-op.
Argument Resolution
If no ID is provided, or the ID doesn't match an active research topic:
- List research specs in
03-in-progress/,04-in-evaluation/, and06-paused/ - If a partial ID or name was given, filter to matches
- Present the matching topics and ask the user to choose one
ARGUMENTS: {{args}}
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 · 34 lines · 17 tokens per session scan A 6f5c56adc7a8
arr is a command published in the GitHub repository jayvee/aigon (26 stars, last pushed 12d ago), licensed Apache-2.0. It adds 17 tokens to every session and 263 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to research-reset, differing in 2 lines, and is treated as a copy.
Other commands, from other repositories
brain-stats
Show claudectl brain learning metrics — accuracy, correction rate, and effectiveness.
stop
Gracefully close the Vibe Squad tmux session from inside Chrono.
mach12:issue-review
Read a GitHub issue and all comments, review the implementation plan, and present findings.
mach12:gh-pr-read
Read a GitHub pull request's title, body, and all top-level PR conversation comments; optionally locate an HTML-marker comment.
scramjet:troubleshoot
Diagnose unexpected command behavior and recommend safe resolution.
checklist
Generate a custom checklist for the current feature based on user requirements.