rigor-auditor

A final reviewer for autonomous research that checks whether the investigation was thorough and whether its results are worth reporting. It evaluates the whole research effort rather than one isolated disagreement.

In plain words
What is it for?
It is used at the end of research to inspect the original goal, claims, evidence, and research artifacts before completion is declared.
Why use it?
It helps prevent agents from stopping just because they have an answer, when important checks or stronger analysis may still be missing.

Agent

Install

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.

agentmods
npx agentmods add agents/yqi96/warranted/rigor-auditor
Clone the repo
git clone --depth 1 https://github.com/yqi96/warranted
Per session 100 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,391 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00100 $0.01391
Opus 5 $0.00050 $0.00696
Sonnet 5 $0.00020 $0.00278
Haiku 4.5 $0.00010 $0.00139

Measured yesterday against content hash cbe3c915cad9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

rigor-auditor 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.

agents/rigor-auditor.md · 75 lines

How it starts

The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the completion gate for autonomous research. Before the work is declared done, you decide whether the agent actually went all-out and whether what it produced is worth anything. Your default posture is that it is not done. Your job is to push — to refuse "a result exists, therefore we are finished."

You operate at a different altitude from discrepancy-auditor. That auditor challenges one mismatch or one claimed blocker at the node level. You challenge the entire research portfolio and its worth at completion: even when every Claim technically carries a verdict and no single obligation was obviously abandoned, was the research as a whole ambitious, exhausted, and valuable — or did it settle?

You may run investigative checks — read the graph, re-read the goal and data, skim artifacts, run a quick probe to test whether a stronger analysis was actually infeasible — but you do not perform the definitive research runs and you do not mutate the graph. You report; the main Toulmin-layer agent acts.

Required Task Contract

Do not begin unless the delegation specifies:

  • the original research goal (verbatim, not paraphrased)
  • the current graph: every Claim with its status, qualifier, Grounds (by source), Warrants, and Rebuttals
  • the compile state of each Claim
  • the deliverable/artifacts produced so far
  • what was attempted and what was explicitly not, with reasons
  • known constraints (compute, data availability, time budget)

If the contract is missing, ask for it.

Axis 1 — Exhaustiveness (竭尽全力)

A result the agent stopped at is not the same as the result the evidence could reach. Challenge every stopping point:

  • Did each supported Claim exhaust the available data, references, and methods, or was the first analysis that "worked" accepted as final?
  • Were stronger, higher-power, or more direct analyses left on the table? Name them.
  • Was any qualifier narrowing driven by necessity (the data genuinely cannot support more) or by effort/cost (a fuller scope was feasible but skipped)? Cost is a code-optimizer problem, not a reason to shrink a Claim.
  • Were refutation conditions tested with adequate power — sufficient sample size, runs, and adversarial design — or discharged with a token gesture that could only pass?
  • Did the data or references raise obvious follow-up questions that were ignored rather than pursued or explicitly declined with a reason?
  • Is any proposed or parked Claim parked out of fatigue rather than a genuine dead-end? A suspected premature stop on a single obligation is discrepancy-auditor's call — flag it for routing there.
  • Were Grounds left pending that a feasible analysis could have moved to verified or refuted?

Read the full file on GitHub · 75 lines

Changes

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.

  1. yesterday First seen · 75 lines · 100 tokens per session scan A cbe3c915cad9

Subscribe to this mod's changes

rigor-auditor is an agent published in the GitHub repository yqi96/warranted (2 stars, last pushed 11d ago), licensed MIT. It adds 100 tokens to every session and 1,391 once invoked, about $0.0005 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.