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 commands/baleen37/bstack/autoresearchgit clone --depth 1 https://github.com/baleen37/bstackWhat 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 | $0.00007 | $0.00438 |
| Opus 5 | $0.00003 | $0.00219 |
| Sonnet 5 | $0.00001 | $0.00088 |
| Haiku 4.5 | $0.00001 | $0.00044 |
Grade A, and why
autoresearch 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 yesterday.
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
Autoresearch Command
You are starting or resuming an autonomous experiment. The default is one iteration and then stop.
Use loop only when the user explicitly requests repeated unattended iterations.
Handle arguments
Arguments: $ARGUMENTS
If arguments = "off"
Create a .autoresearch/off sentinel file in the current directory:
mkdir -p .autoresearch && touch .autoresearch/off
Then tell the user autoresearch mode is paused. It can be resumed by running /autoresearch again (which will delete the sentinel).
If .autoresearch/autoresearch.md exists in the current directory (resume)
This is a resume. Do the following:
- Delete
.autoresearch/offif it exists - Read
.autoresearch/autoresearch.mdto understand the objective, constraints, and what's been tried - Read
.autoresearch/results.jsonlto reconstruct state:- Count total runs, kept, discarded, crashed
- Find the baseline metric (first data row)
- Find the best metric and which commit achieved it
- Note which secondary metric columns are being tracked
- Read recent git log:
git log --oneline -20 - If
.autoresearch/ideas.mdexists, read it for experiment inspiration - Perform exactly one next experiment, then stop. If the arguments explicitly include
loop, use.autoresearch/loop.shwith the requested runtime and iteration limit.
If .autoresearch/autoresearch.md does NOT exist (fresh start)
- Delete
.autoresearch/offif it exists - Invoke the
autoresearchskill to set up the experiment from scratch - If arguments were provided (other than "off"), use them as the goal description to skip/answer the setup questions
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.
- yesterday First seen · 52 lines · 7 tokens per session scan A 53b95d6c3c10
autoresearch is a command published in the GitHub repository baleen37/bstack (4 stars, last pushed 12d ago), licensed MIT. It adds 7 tokens to every session and 438 once invoked, about $0.0000 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 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.