reward_judge_operational

reward_judge_operational is a skill for Claude Code, Codex from Qwen-Applications/Skill-RM. It costs 79 tokens per session (1,423 once invoked), scanned A, original, Apache-2.0.

A resource-based procedure for judging candidate answers. It can use visible task metadata, references, checklists, verifier results, and other evidence when those resources are available.

In plain words
What is it for?
Inspecting judging resources, applying relevant evidence and bias controls, running permitted verification steps, and returning the required verdict format.
Why use it?
It supports more reliable decisions when answer quality depends on facts, formal requirements, or automated checks.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Inspecting judging resources, applying relevant evidence and bias controls, running permitted verification steps, and returning the required verdict format.

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Install with agentmods
npx agentmods add skills/qwen-applications/skill-rm/reward_judge_operational
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.

Any agent
npx skills add Qwen-Applications/Skill-RM --skill reward_judge_operational
Clone the repo
git clone --depth 1 https://github.com/Qwen-Applications/Skill-RM

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for reward_judge_operational

README.md
[![agentmods](https://agentmods.dev/badge/skills/qwen-applications/skill-rm/reward_judge_operational/github.svg)](https://agentmods.dev/skills/qwen-applications/skill-rm/reward_judge_operational)
Your own site
<a href="https://agentmods.dev/skills/qwen-applications/skill-rm/reward_judge_operational"><img src="https://agentmods.dev/badge/skills/qwen-applications/skill-rm/reward_judge_operational/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.

agentmods 80×15 button for reward_judge_operational

Your own site · 80×15
<a href="https://agentmods.dev/skills/qwen-applications/skill-rm/reward_judge_operational"><img src="https://agentmods.dev/badge/skills/qwen-applications/skill-rm/reward_judge_operational.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 79 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,423 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00079 $0.01423
Opus 5 $0.00039 $0.00711
Sonnet 5 $0.00016 $0.00285
Haiku 4.5 $0.00008 $0.00142

Measured 11d ago against content hash e3f484ff744e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

reward_judge_operational 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 11d 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.

skills/reward_judge_operational/SKILL.md · 111 lines

How it starts

The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Reward Judge

Use this skill to organize and access reward-judging resources. The skill is a controller and resource interface, not a per-sample prompt template.

This skill has one clean operational path: inspect the visible resource index, use only resources listed for the current sample, and produce the required verdict JSON.

Inputs

The host message provides the visible judging task:

  • benchmark and task metadata, when the operational setting allows it;
  • user prompt or instruction;
  • candidate responses and their current labels;
  • required final output format.

Hidden chosen/rejected/gold/test labels are not available and must not be inferred.

Resource Interface

After this skill is loaded, inspect the resource index. Use only resources that can materially affect the verdict.

Common resource types:

  • rubric: benchmark or task criteria.
  • principle: high-level judging principles.
  • metadata: visible benchmark/task metadata.
  • reference: visible reference answer or ground truth.
  • checklist: visible constraints, criteria, or checklist items.
  • verifier: runnable or documented verifier signal over visible content.
  • tool: runnable tool over visible content, such as python_sandbox.
  • tool_protocol: code, math, or factuality verification protocol.
  • external_pipeline: same-backbone judging pipeline evidence exposed by the current run.
  • calibration: position, verbosity, style, and confidence-bias controls.
  • aggregation: policy for combining conflicting evidence.

Prefer resource reads in this order when relevant:

  1. Visible hard evidence: reference, ground truth, checklist, executable verifier, or test-case evidence.
  2. Reliable same-backbone external pipeline output.
  3. Benchmark/task-specific rubric and principles.
  4. Bias-control and aggregation resources for close calls.

Do not read every resource. For ordinary clear cases, direct judgment is acceptable. For close, exact, or correctness-sensitive cases, load only the few resources needed.

Read the full file on GitHub · 111 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. 11d ago First seen · 111 lines · 79 tokens per session scan A e3f484ff744e

Subscribe to this mod's changes

reward_judge_operational is a skill published in the GitHub repository Qwen-Applications/Skill-RM (25 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 79 tokens to every session and 1,423 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.

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