Agent skill

Autoresearch Task Authoring

by bosprimigenious in bosprimigenious/autoresearch-skills

从论文与代码仓设计可交付的 AutoResearch 工程题,确定 Starter、Baseline、Reference、评分器、Harbor 结构和证据契约。用于出题、改题或审题;不替代提交包最终 QA。

MITAuto-check passedAgent Workflows

Install Autoresearch Task Authoring

skills CLI
$ npx skills add bosprimigenious/autoresearch-skills --skill autoresearch-task-authoring -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install bosprimigenious/autoresearch-skills autoresearch-task-authoring --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/bosprimigenious/autoresearch-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/autoresearch-task-authoring .claude/skills/autoresearch-task-authoring && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
autoresearch-task-authoring
GitHub stars
153
Token cost
~390 tokens
SKILL.md length
89 words
Files
8 (incl. scripts, references)
Skills in repo
8
Repo updated
First seen
Licence
MIT

At a glance

从论文与代码仓设计可交付的 AutoResearch 工程题,确定 Starter、Baseline、Reference、评分器、Harbor 结构和证据契约。用于出题、改题或审题;不替代提交包最终 QA。

  • Works in 9 steps: 建立题目合同:允许修改面、冻结面、输入输出、预算、质量门、主指标方向和 0/1… → Starter 必须朴素、可运行且不故意削弱;Baseline… → Reference 只能证明题目有改进空间,不能把算法答案写进… → …
  • Tasks that involve Autonomous loops
  • Runs Python scripts from its folder; calls python3

What it does

Autoresearch Task Authoring is an agent skill from bosprimigenious/autoresearch-skills. 从论文与代码仓设计可交付的 AutoResearch 工程题,确定 Starter、Baseline、Reference、评分器、Harbor 结构和证据契约。用于出题、改题或审题;不替代提交包最终 QA。

Its SKILL.md is about 390 tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `AGENTS.md`, `CLAUDE.md` and `agents/openai.yaml`).

It sits in Agent Workflows, covering Autonomous loops. The repository describes itself as: Reusable skills for AutoResearch task design, isolation, QA, and handoff. The licence is MIT.

When your agent uses it

  • Tasks that involve Autonomous loops

Example prompts

  • “/autoresearch-task-authoring”

Requirements

  • Python 3
  • Docker

Workflow steps

9 steps, taken from the first numbered list in SKILL.md.

  1. 建立题目合同:允许修改面、冻结面、输入输出、预算、质量门、主指标方向和 0/1 锚点。完成论文身份、许可、优化面和当前权威题库证据后运行 scripts/authoring_gate.py selection evidence.json。
  2. Starter 必须朴素、可运行且不故意削弱;Baseline 必须来自正式实现并能解释。
  3. Reference 只能证明题目有改进空间,不能把算法答案写进 instruction;正式 B/R 使用相同数据、seed、预算和评测器。
  4. 评分器从候选代码重新运行并独立计算结果,不采信候选自报分数;成功结果用同文件系统 stage 后原子替换。
  5. 将作者材料、参赛者 workspace 和优化证据分开。Docker COPY、WORKDIR、入口与选定的平台 profile 必须形成一条可执行路径。
  6. 先做小规模成对实跑,再决定是否值得开展双轨迹长跑。完成 Baseline/Reference、效应/噪声和独立复算后过 pilot 门;完成双镜像、Hidden 隔离和目标 Harness trial 后过 container 门。没有动态证据时明确写“未验证运行”。
  7. 双轨迹分别保存正式血缘与失败轮,完成机外快照和恢复演练后过 long_run 门。失败必须用新 trial 修复,不覆盖旧 receipt 或拼接不同轮次证据。
  8. 交付前使用 autoresearch-qa-skills-0.3.4 做双路独立本地质检。冻结唯一完整提交包 ZIP 及 SHA256;两种不同 AI 分别新建无历史上下文的会话,每个会话只发该 ZIP。不同模型家族优先,同类 AI…
  9. 开源或外发前对主包、QA/self-check、轨迹和证据附件分别做隐私与可移植性检查;生成报告不得保留作者 home、凭据值或私有文件链接。按 出题合同 生成 release-evidence.json,再运行 python3…

What it can do on your machine

Read from SKILL.md and the folder at commit d8ff7e2. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Autoresearch Task Authoring loads about 390 tokens when it runs, and up to ~2.1k if it reads all its reference files. Until then it costs about 33 tokens; SKILL.md has 89 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~33
When it runs · the whole SKILL.md, loaded when a task matches
~390
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from bosprimigenious/autoresearch-skills at commit d8ff7e2, republished under its MIT licence (© bosprimigenious). 89 words, ~390 tokens.

Download SKILL.mdSave it as .claude/skills/autoresearch-task-authoring/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
autoresearch-task-authoring
description
从论文与代码仓设计可交付的 AutoResearch 工程题,确定 Starter、Baseline、Reference、评分器、Harbor 结构和证据契约。用于出题、改题或审题;不替代提交包最终 QA。

AutoResearch 出题

先读任务平台最新规则、项目示例和目标论文,再读 authoring-contract.md 与 前移 QA。不得从旧题或别的仓库复制未经验证的结构。

  1. 建立题目合同:允许修改面、冻结面、输入输出、预算、质量门、主指标方向和 0/1 锚点。完成论文身份、许可、优化面和当前权威题库证据后运行 scripts/authoring_gate.py selection evidence.json。
  2. Starter 必须朴素、可运行且不故意削弱;Baseline 必须来自正式实现并能解释。
  3. Reference 只能证明题目有改进空间,不能把算法答案写进 instruction;正式 B/R 使用相同数据、seed、预算和评测器。
  4. 评分器从候选代码重新运行并独立计算结果,不采信候选自报分数;成功结果用同文件系统 stage 后原子替换。
  5. 将作者材料、参赛者 workspace 和优化证据分开。Docker COPY、WORKDIR、入口与选定的平台 profile 必须形成一条可执行路径。
  6. 先做小规模成对实跑,再决定是否值得开展双轨迹长跑。完成 Baseline/Reference、效应/噪声和独立复算后过 pilot 门;完成双镜像、Hidden 隔离和目标 Harness trial 后过 container 门。没有动态证据时明确写“未验证运行”。
  7. 双轨迹分别保存正式血缘与失败轮,完成机外快照和恢复演练后过 long_run 门。失败必须用新 trial 修复,不覆盖旧 receipt 或拼接不同轮次证据。
  8. 交付前使用 autoresearch-qa-skills-0.3.4 做双路独立本地质检。冻结唯一完整提交包 ZIP 及 SHA256;两种不同 AI 分别新建无历史上下文的会话,每个会话只发该 ZIP。不同模型家族优先,同类 AI 的不同版本也可以。不附带散文件、旧报告、作者解释或另一 AI 的结论。两路首轮质检均须完整实测;任一路命中硬失败或分歧未闭环即 NOT READY。审查报告是 release 门的输入,不能由作者原会话内自报结论替代。
  9. 开源或外发前对主包、QA/self-check、轨迹和证据附件分别做隐私与可移植性检查;生成报告不得保留作者 home、凭据值或私有文件链接。按 出题合同 生成 release-evidence.json,再运行 python3 scripts/authoring_gate.py release release-evidence.json。门禁会读取并校验两份 QA 报告、共识、隐私报告和 manifest 的内容与 SHA256;任一引用缺失、摘要被篡改、模型或会话不独立、ZIP 不同源或有未解决分歧都必须失败。

输出至少包括题面、接口、Starter、Baseline、Reference、评分器、冻结清单、证据清单、构建说明和验收命令。

© bosprimigenious, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts, references) in skills/autoresearch-task-authoring of bosprimigenious/autoresearch-skills.

  • SKILL.md
  • AGENTS.md
  • CLAUDE.md
  • agents/openai.yaml
  • references/authoring-contract.md
  • references/shift-left-qa.md
  • scripts/authoring_gate.py
  • scripts/test_authoring_gate.py

Open the folder on GitHubat commit d8ff7e2

Compare with similar skills

Autoresearch Task Authoring next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Autoresearch Task Authoring compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Autoresearch Task Authoring this skillbosprimigenious/autoresearch-skills153—~390Automated safety check: PassMIT
Show Me Your Work Decision Logcursor/plugins11k8 repos~1.6kAutomated safety check: PassNone
Autoresearch Iteration Loopuditgoenka/autoresearch6.5k1 repos~2kAutomated safety check: PassMIT
Install Loop Engineeringcobusgreyling/loop-engineering11k1 repos~648Automated safety check: PassMIT
LoopyForward-Future/loopy3.2k—~3.9kAutomated safety check: PassMIT
AI Performance Improvement Plantanweai/pua20k2 repos~6.9kAutomated safety check: PassMIT

Similar skills

  • Official

    Keeps a TSV decision log for long or unattended agent runs, one row per decision with what, why, evidence and result, so a reviewer can check the work later.

    11k GitHub starsUsed in 8 repos~1.6k tokens
    Agent WorkflowsAuto-check passed
  • Autoresearch Iteration Loop

    uditgoenka/autoresearch

    Runs an autonomous modify, verify, keep-or-discard loop against any metric, with subcommands for planning, debugging, fixing, security audits, shipping and more.

    6.5k GitHub starsUsed in 1 repo~2k tokens
    Agent WorkflowsAuto-check passed
  • Install Loop Engineering

    cobusgreyling/loop-engineering

    Installs Loop Engineering into a project through the single @cobusgreyling/loop CLI, scaffolding a report-only loop and a readiness score.

    11k GitHub starsUsed in 1 repo~648 tokens
    Agent WorkflowsAuto-check passed
  • Loopy

    Forward-Future/loopy

    Discover, find, compare, audit, repair, adapt, craft, run, debrief, save, and prepare repeatable AI-agent loops for publication.

    3.2k GitHub stars~3.9k tokensUpdated 29 days ago
    Agent WorkflowsAuto-check passed
  • Pushes an agent to exhaust every option, investigate before asking and take initiative beyond the literal request, instead of giving up or waiting passively.

    20k GitHub starsUsed in 2 repos~6.9k tokens
    Agent WorkflowsAuto-check passed
  • LoopX Self Repair

    loopx-project/loopx

    Diagnoses surprising LoopX behavior, such as stale recommendations or tiny progress, assigns it to the responsible layer and repairs it at the lowest durable level.

    6.2k GitHub stars~2.2k tokensUpdated today
    Agent WorkflowsAuto-check passed

More from bosprimigenious/autoresearch-skills

All 8 skills in this repo
  • Autoresearch Baseline Quality

    bosprimigenious/autoresearch-skills

    对 AutoResearch 的正式 Baseline 做只读合理性审查,检查训练不足、实现故障、预算或 seed 不公平及缺乏代表性的弱对照,区分合理 naive Starter 与评分锚点。适用于专家提交包和 Baseline/Reference 证据复核,不用于求解任务或要求 Baseline 达到 SOTA。

    153 GitHub stars~1.1k tokensUpdated 5 days ago
    Auto-check passed
  • Autoresearch Paper Discovery

    bosprimigenious/autoresearch-skills

    自主检索、去重并筛选可转化为 AutoResearch 优化任务的论文,核查论文与源码许可、优化面、评测、资源、效应噪声和目标 Harness 可交付性。用于从零找论文、维护候选池或在投入实现前做选题预检;不用于已经确定论文后的实验执行。

    153 GitHub stars~506 tokensUpdated 5 days ago
    Auto-check passed
  • Autoresearch Task QA

    bosprimigenious/autoresearch-skills

    对 AutoResearch 目录或 ZIP 做只读质检;先审优化面是否仅调参、Baseline 是否合理、Reference 提升是否充分,再查 21 项实现、严格 Docker 路径、Harbor 接口与成对训练证据。输出方法介绍、完整跑分、专家退回说明及 TXT/Markdown/JSON 报告;不用于求解任务。

    153 GitHub stars~1.6k tokensUpdated 5 days ago
    Auto-check passed
  • Autoresearch Run Isolation

    bosprimigenious/autoresearch-skills

    为 AutoResearch 的双 Agent 轨迹、付费 GPU 长跑、Docker 执行、可信评测与恢复建立共享协议、成本决策和隔离边界。用于小时/包日选择、启动或恢复 campaign、设计证据与防止题目或轨迹串用;不替代具体任务算法或最终平台 QA。

    153 GitHub stars~553 tokensUpdated 5 days ago
    Auto-check passed
  • Autoresearch Feishu Three Table

    bosprimigenious/autoresearch-skills

    在已获授权的飞书/Lark 多维表格中处理 AutoResearch 的领题、完成提交/验收和组长初检三表流转,核对当期题号、字段权限、证据和写后回读。用于领取题目、提交验收材料或回填初检结论;不用于绕过组织权限、恢复离职账号或替代任务 QA。

    153 GitHub stars~413 tokensUpdated 5 days ago
    Auto-check passed
  • Autoresearch Conversation Handoff

    bosprimigenious/autoresearch-skills

    将 AutoResearch 的 Claude、Codex、Cursor 对话、命令输出和外部提交状态整理为可执行交接,区分事实、失败、待办和证据边界。用于总结长会话、换 agent 或收尾归档;不把对话陈述当作已验证事实。

    153 GitHub stars~183 tokensUpdated 5 days ago
    Auto-check passed

Categories

Questions about Autoresearch Task Authoring

What does Autoresearch Task Authoring do?

从论文与代码仓设计可交付的 AutoResearch 工程题,确定 Starter、Baseline、Reference、评分器、Harbor 结构和证据契约。用于出题、改题或审题;不替代提交包最终 QA。. Autoresearch Task Authoring is an agent skill from bosprimigenious/autoresearch-skills.

When should I use Autoresearch Task Authoring?

Autoresearch Task Authoring fits situations like: tasks that involve Autonomous loops.

How do I install Autoresearch Task Authoring in Claude Code?

Run `npx skills add bosprimigenious/autoresearch-skills --skill autoresearch-task-authoring -a claude-code`. Or copy the skill folder (skills/autoresearch-task-authoring in bosprimigenious/autoresearch-skills) into .claude/skills/autoresearch-task-authoring in your project. Claude Code loads it when a task matches its description.

How do I install Autoresearch Task Authoring in Codex?

Run `npx skills add bosprimigenious/autoresearch-skills --skill autoresearch-task-authoring -a codex`. Or copy the skill folder (skills/autoresearch-task-authoring in bosprimigenious/autoresearch-skills) into .agents/skills/autoresearch-task-authoring in your project. Codex loads it when a task matches its description.

Can I use Autoresearch Task Authoring in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add bosprimigenious/autoresearch-skills --skill autoresearch-task-authoring -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/autoresearch-task-authoring, .gemini/skills/autoresearch-task-authoring, .github/skills/autoresearch-task-authoring and .opencode/skills/autoresearch-task-authoring in your project.

What does Autoresearch Task Authoring need to run?

Going by SKILL.md and its folder, Autoresearch Task Authoring needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3; Docker.

Does Autoresearch Task Authoring access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Autoresearch Task Authoring safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Autoresearch Task Authoring use?

Autoresearch Task Authoring is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Autoresearch Task Authoring use?

About 390 tokens (SKILL.md is roughly 1.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.7k tokens, read only when the agent opens those files.

What are the alternatives to Autoresearch Task Authoring?

Skills that share tags, products or a category with Autoresearch Task Authoring: Show Me Your Work Decision Log (cursor/plugins, 11k stars), Autoresearch Iteration Loop (uditgoenka/autoresearch, 6.5k stars), Install Loop Engineering (cobusgreyling/loop-engineering, 11k stars) and Loopy (Forward-Future/loopy, 3.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Autoresearch Task Authoring?

bosprimigenious (a GitHub user) maintains it in bosprimigenious/autoresearch-skills, which has 153 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on October 4, 2026.

Source: bosprimigenious/autoresearch-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.