360 Secure SkillHub
360 安全技能中心

gauntlet-curate

读取题库目录下的 YAML 文件与 _manifest.yaml 预期题量清单,统计各分类实际题量并与目标数量对比,找出缺口最大的分类,再按既定 schema 起草新题目条目,最终输出一份 Markdown 报告交人工审核。Skill 明确禁止直接改写题库文件,也不提供写入或自动修复选项。

athola
athola
热度 54.59
最近更新 2026-08-26 21:12:27
分类:知识依赖:代码执行 / 读写文件 / 内部调用大模型应用场景:报告撰写 / 研究 / 测验 / 模板

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add nm-gauntlet-gauntlet-curate
Metadata
name
gauntlet-curate
description
Audits the DSA problem bank for coverage gaps and proposes new YAML entries
version
1.9.8
triggers
["refreshing the problem bank during update-plugins runs"]
metadata
{"openclaw":{"homepage":"https://github.com/athola/claude-night-market/tree/master/plugins/gauntlet","emoji":"🦞"}}
source
claude-night-market
source_plugin
gauntlet

Night Market Skill — ported from claude-night-market/gauntlet. For the full experience with agents, hooks, and commands, install the Claude Code plugin.

Gauntlet Curate

Survey the DSA problem bank, identify coverage gaps, and propose new YAML entries for human review.

When This Skill Fires

Invoke this skill manually with Skill(gauntlet:gauntlet-curate) when the problem bank needs a coverage review. The skill is intended to participate in /update-plugins runs but is not yet wired into that command (see openpackage.yml registration). It is distinct from gauntlet:curate, which handles per-annotation knowledge capture and is what /gauntlet-curate invokes today.

Steps

  1. Locate the problem bank at plugins/gauntlet/data/problems/. Read _manifest.yaml to load the expected NeetCode counts per category.

  2. Survey current coverage by counting problems in each YAML file (skipping _manifest.yaml). Run the analysis script:

    cd plugins/gauntlet
    python scripts/curate_problems.py data/problems/ --output /tmp/gauntlet-curate-report.md
    
  3. Identify gaps: categories whose actual count falls below the neetcode_count in the manifest. The script sorts gaps largest-first so the worst shortfalls appear at the top.

  4. Review existing problems in each gap category to understand what is already covered before proposing additions.

  5. Propose new YAML entries following the schema below. Add proposals to the report under "Proposed New Problems". Do NOT write proposals directly into data/problems/*.yaml.

  6. Validate proposals by running:

    python -c "
    import yaml, sys
    sys.path.insert(0, 'src')
    from gauntlet.models import BankProblem
    proposals = yaml.safe_load(open('proposals.yaml'))
    for p in proposals:
        BankProblem.from_dict(p)
    print('All proposals valid.')
    "
    
  7. Present the report to the human for review. The report includes the coverage table, gap list, and proposed entries. The human decides which proposals to merge into the YAML files.

Problem Schema

Each proposed entry must follow this schema:

- id: category-NNN
  title: Problem Title
  difficulty: easy       # easy | medium | hard | extra_hard
  prompt: |
    Problem statement with constraints and examples.
  hints:
    - First hint.
    - Second hint.
  solution_outline: |
    Approach and time/space complexity.
  tags: [tag1, tag2]
  neetcode_id: neetcode-NNN
  challenge_type: explain_why  # explain_why | multiple_choice | trace
                                # | code_complete | debug | rank

Required fields: id, title, difficulty, prompt. Optional fields default to empty values.

Safety Constraints

  • Never modify files under data/problems/ directly.
  • Never run with a --write or --fix flag: the script intentionally has none.
  • All output is a proposal report for human approval.
  • Existing hand-curated problems are never touched.

Output

A markdown report at the path specified by --output, containing:

  • Coverage summary table (expected vs. actual per category)
  • Gaps list sorted by missing count
  • YAML schema template for new proposals
  • Space for the human reviewer to add proposed entries

Human review is required before any YAML file changes.