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/yqi96/warranted/auto-researchnpx skills add yqi96/warranted --skill auto-researchgit clone --depth 1 https://github.com/yqi96/warrantedWrote 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/yqi96/warranted/auto-research)<a href="https://agentmods.dev/skills/yqi96/warranted/auto-research"><img src="https://agentmods.dev/badge/skills/yqi96/warranted/auto-research.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 5.1 | $0.00070 | $0.02623 |
| Opus 5 | $0.00035 | $0.01311 |
| Sonnet 5 | $0.00014 | $0.00525 |
| Haiku 4.5 | $0.00007 | $0.00262 |
Grade A, and why
auto-research 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 6d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Channel
You are handed a research goal plus reference material and data, and no fixed argument to extract. The graph is the counterweight. Every question you raise gets a structural home, every conclusion must be earned through evidence, inference, rebuttal handling, and compile — never asserted because the analysis "looked right."
Framing Router
The first decision is where the Claims come from. Test each input proposition: could it be shown false?
- Weak Framing — the input already states a specific question or a specific expected answer to test. Cast the question's answer as a Claim; cast a user-stated expected answer as a
source="observed"Statement (verificationpending). Do not re-decompose; the target is given, so proceed like a bounded reproduction. - Strong Framing — the input is a research goal or direction with no pre-stated falsifiable answer. Decompose it into a small set of answerable research questions, then
create_claim(status startsproposed) — one Claim per question whose verdict matters. Because nothing external fixes the target, the falsification obligation below is mandatory before any evidence run. - Mixed input — apply Weak Framing to the stated parts and Strong Framing to the gaps.
Keep the initial Claim set small and load-bearing. Over-proposing Claims you never test is the same failure as testing none.
Graph Mapping
research goal / question -> one or more research questions
a falsifiable answer to a question -> Claim (status=proposed)
a proposed or expected answer -> Statement(source="observed", verification="pending")
a result computed from the given data -> Statement(source="observed") as Ground
a citable proposition from a reference -> Statement(source="literature") as Ground or Backing
"what result would show this Claim false" -> a pre-registered refutation condition, tested as a Rebuttal candidate
why the evidence authorizes the conclusion -> Warrant
the method or standard behind the inference -> Statement as Backing
a confirmed conflict against Claim or Warrant-> Statement(rebuttal_for={target_id, target_type})
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.
- 6d ago First seen · 126 lines · 70 tokens per session scan A 41cb82b5a5a4
auto-research is a skill published in the GitHub repository yqi96/warranted (2 stars, last pushed 4d ago), licensed MIT. It adds 70 tokens to every session and 2,623 once invoked, about $0.0003 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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