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 agentmods add skills/waltstephen/argusbot/autonomous-research-loopnpx skills add waltstephen/ArgusBot --skill autonomous-research-loopgit clone --depth 1 https://github.com/waltstephen/ArgusBotWrote 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/waltstephen/argusbot/autonomous-research-loop)<a href="https://agentmods.dev/skills/waltstephen/argusbot/autonomous-research-loop"><img src="https://agentmods.dev/badge/skills/waltstephen/argusbot/autonomous-research-loop.svg" alt="Measured on agentmods" 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 | $0.00079 | $0.01677 |
| Opus 5 | $0.00039 | $0.00839 |
| Sonnet 5 | $0.00016 | $0.00335 |
| Haiku 4.5 | $0.00008 | $0.00168 |
Grade A, and why
autonomous-research-loop 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 4d 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 — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autonomous Research Loop
Overview
Run autonomous engineering and experiment loops with strict acceptance gates. Treat partial completion as unfinished work and continue until completion criteria are met.
Operating Contract
Apply these rules for every run:
- Initialize git context at start.
- Keep repository synchronized if remote exists.
- Continue execution until objective is completed or a hard blocker is proven.
- Validate behavior with runnable checks, not only static edits.
- Commit every meaningful fix.
- Push when remote is configured and credentials allow push.
- Treat tests as hard completion gates, not optional checks.
- In YOLO mode (
--dangerously-bypass-approvals-and-sandbox), assume full execution power and apply extra caution before any destructive command. - Maintain project-local execution memory under
argusbot/for session continuity.
Step 0: Bootstrap Git Safely
Execute at task start:
git init
Then detect repo and remote status:
git rev-parse --is-inside-work-tree
git remote -v
If a remote and tracked branch exist, try to sync before edits:
git pull --rebase --autostash
If pull fails, continue local work and record reason in status updates.
Step 0.5: Create Local Execution Memory
At project root, create and maintain an argusbot/ directory.
Required files:
argusbot/current-session.mdargusbot/todo.mdargusbot/todo_session.md
Update them at start and after every meaningful loop iteration.
argusbot/current-session.md must contain:
- Current objective
- What was completed in this session
- Latest commands run
- Latest validation result
- Latest commit hash
- Current blockers or risks
argusbot/todo.md must contain:
- Remaining work items
- Next highest-priority action
- Any deferred investigation
argusbot/todo_session.md must contain:
- Session-specific objective interpretation
- Completed items in this session
- Remaining items for this session
- Latest operator injects that materially changed scope
- What should be checked first in the next session
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 232 lines · 79 tokens per session scan A 7a1d9839fbe8
autonomous-research-loop is a skill published in the GitHub repository waltstephen/ArgusBot (316 stars, last pushed 4mo ago), licensed MIT. It adds 79 tokens to every session and 1,677 once invoked, about $0.0004 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 skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…