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/ars)<a href="https://agentmods.dev/commands/jayvee/aigon/ars"><img src="https://agentmods.dev/badge/commands/jayvee/aigon/ars/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/ars"><img src="https://agentmods.dev/badge/commands/jayvee/aigon/ars.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 | $0.00020 | $0.00838 |
| Opus 5.5 | $0.00008 | $0.00335 |
| Sonnet 5.5 | $0.00004 | $0.00168 |
| Haiku 4.5 | $0.00002 | $0.00084 |
Grade A, and why
ars 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
97% identical to research-start — 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.
How it starts
The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
aigon-research-start
Prepare your workspace to conduct research in either Drive or Fleet mode.
CRITICAL: You MUST use the CLI command below to perform setup. Do NOT manually move topic files, lifecycle-view links, or create worktrees — the CLI records the workflow transition and prepares worktree state.
Usage
Argument Resolution
If no ID is provided, or the ID doesn't match an existing topic in the backlog:
- List all files in
./docs/specs/research-topics/02-backlog/matchingresearch-*.md - If a partial ID or name was given, filter to matches
- Present the matching topics and ask the user to choose one
Step 1: Run the CLI command
CRITICAL: Run EXACTLY the arguments the user provided. Do NOT add agents that weren't specified.
# Drive mode — user passes only an ID
aigon research-start {{args}}
# Drive worktree mode — user passes ID + agent
aigon research-start {{args}} <agent>
# Fleet mode — user passes ID + 2+ agents
aigon research-start {{args}} <agent1> <agent2> [agent3...]
The mode is determined automatically based on what the user provides:
- No agents: Drive mode - conduct research in the current repo
- 1 agent: Drive worktree mode - create one research worktree
- 2+ agents: Fleet mode - create parallel research worktrees/findings contexts
The CLI will:
- Transition the topic from backlog to in-progress and refresh the generated lifecycle view
- Commit the topic move before any worktree setup
- Create findings files for agents when needed
- Create worktree/session context for parallel research
Step 2: Confirm setup and next steps
Research now follows the same lifecycle shape as features: start -> do -> submit -> eval -> close.
Drive Mode
After the CLI completes, run:
/aigon:research-do <ID>
When the research pass is complete, signal completion with aigon agent-status research-complete, then close with:
/aigon:research-close <ID>
Drive Worktree Mode
After the CLI completes, the research agent session is ready in the worktree context. Run:
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 · 116 lines · 20 tokens per session scan A 544161f41025
ars is a command published in the GitHub repository jayvee/aigon (26 stars, last pushed 12d ago), licensed Apache-2.0. It adds 20 tokens to every session and 838 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to research-start, differing in 2 lines, and is treated as a copy.
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