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 skills add jayvee/aigon --skill aigon-research-autopilotgit 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/skills/jayvee/aigon/aigon-research-autopilot)<a href="https://agentmods.dev/skills/jayvee/aigon/aigon-research-autopilot"><img src="https://agentmods.dev/badge/skills/jayvee/aigon/aigon-research-autopilot/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/skills/jayvee/aigon/aigon-research-autopilot"><img src="https://agentmods.dev/badge/skills/jayvee/aigon/aigon-research-autopilot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 54 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00026 | $0.00568 |
| Opus 5 | $0.00013 | $0.00284 |
| Sonnet 5 | $0.00005 | $0.00114 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
aigon-research-autopilot 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
aigon-research-autopilot
Run a fully autonomous Fleet research pipeline. Sets up findings files, spawns agents in parallel, monitors progress, and optionally runs synthesis when all agents submit.
aigon research-autopilot $ARGUMENTS [agents...]
Argument Resolution
If no ID is provided, or the ID doesn't match an existing topic in backlog or in-progress:
- List all files in
./docs/specs/research-topics/02-backlog/and03-in-progress/matchingresearch-*.md - If a partial ID or name was given, filter to matches
- Present the matching topics and ask the user to choose one
Usage
Basic usage (use configured default agents)
aigon research-autopilot $ARGUMENTS
Specify agents explicitly
aigon research-autopilot $ARGUMENTS cc ag cx
With auto-eval
aigon research-autopilot $ARGUMENTS cc ag cx --auto-eval
What it does
- Setup phase: If no findings files exist, runs
research-startto create them - Spawn phase: Creates a tmux session for each agent, running
research-do - Monitor phase: Polls agent findings files every 30s for
completestatus, prints status table - Evaluate phase: If
--auto-eval, runsresearch-evalautomatically; otherwise prints the command
Subcommands
aigon research-autopilot status $ARGUMENTS # Check agent statuses
aigon research-autopilot stop $ARGUMENTS # Stop all agents
Options
--auto-eval— Automatically runresearch-evalwhen all agents submit--poll-interval=N— Seconds between status checks (default: 30)
Requirements
- tmux must be installed (
brew install tmux) - At least 2 agents must be specified (or configured as defaults)
- Research topic must be in backlog or in-progress
Agent Workflow
Each spawned agent will:
- Run
research-doto conduct their research - Write findings to their findings file
- Run
agent-status research-completeto signal completion
Prompt Suggestion
After all agents submit, suggest the eval command:
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.
- 8d ago First seen · 77 lines · 26 tokens per session scan A 38c63fdc86cb
aigon-research-autopilot is a skill published in the GitHub repository jayvee/aigon (25 stars, last pushed 7d ago), licensed Apache-2.0. It adds 26 tokens to every session and 568 once invoked, about $0.0001 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.
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