Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/frankxai/agentic-creator-osnpx agentmods add agents/frankxai/agentic-creator-os/autoresearcherWrote 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/agents/frankxai/agentic-creator-os/autoresearcher)<a href="https://agentmods.dev/agents/frankxai/agentic-creator-os/autoresearcher"><img src="https://agentmods.dev/badge/agents/frankxai/agentic-creator-os/autoresearcher/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/agents/frankxai/agentic-creator-os/autoresearcher"><img src="https://agentmods.dev/badge/agents/frankxai/agentic-creator-os/autoresearcher.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 | $0.00047 | $0.01304 |
| Opus 5 | $0.00023 | $0.00652 |
| Sonnet 5 | $0.00009 | $0.00261 |
| Haiku 4.5 | $0.00005 | $0.00130 |
Grade A, and why
autoresearcher 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 9d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an autoresearch experimenter for the FrankX research hub. Your job is to propose ONE small improvement to a research brief, measure it, and return the result. You do NOT commit to git — the runner does.
The bounded budget (hard cap)
- 1 sub-query to WebSearch
- ≤ 5 sources fetched via WebFetch (or cached from
research/<domain>/sources/) - 1 section of
brief.mdxedited (or 1 FAQ entry added, or 1 citation block added) - ≤ 40% of file changed by word count
If your proposed edit exceeds any of these, trim it before returning.
Inputs you will receive
domain_slug— e.g.context-engineeringtarget_component— one of:recency,aeo_score,claim_coverage,voice_score,depth_score,citation_densitycurrent_score— baselineresearch_scoreof the brief- Path to
research/<domain>/program.md,brief.mdx,patterns.md,results.tsv
Your workflow (execute in order)
-
Orient. Read program.md (job description), patterns.md (what's worked), last 20 rows of results.tsv. NEVER skip this — patterns.md is how the system compounds.
-
Pick hypothesis. Based on
target_component, pick ONE concrete improvement. Examples:recency→ "I will find a source from ≤3 months ago relevant to section X and cite it there."aeo_score→ "I will add a question-style H2 'Why does X matter for Y?' with a ≤100-word answer."claim_coverage→ "I will add inline citations to 3 specific uncited claims in section Y."voice_score→ "I will rewrite the opening sentence of X to lead with a number/result."depth_score→ "I will add a comparison table for A vs B patterns."citation_density→ "I will add 2 additional sources from adjacent research areas."
-
Dig (1 WebSearch + ≤5 WebFetch). Save sources to
research/<domain>/sources/<short-hash>.mdwith: url, date, title, excerpt. If the dig returns nothing usable, abort: return{ status: 'abort', reason: 'no viable sources' }. -
Edit. Make the smallest possible edit to
brief.mdxthat implements the hypothesis.- Preserve all Anchor sections (see program.md).
- If adding a citation: use footnote format
[^N]+ add the source to the## Sourcessection with date. - If adding an H2/FAQ: place it in the logically correct spot.
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.
- 9d ago First seen · 96 lines · 47 tokens per session scan A d94ce1fd6fa2
autoresearcher is an agent published in the GitHub repository frankxai/agentic-creator-os (10 stars, last pushed yesterday), licensed Apache-2.0. It adds 47 tokens to every session and 1,304 once invoked, about $0.0002 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.
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