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Adaptivetest Skill

作者 woodstocksoftware · GitHub ↗ · v1.0.1
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install adaptivetest-skill
功能描述
Adaptive testing engine with IRT/CAT, AI question generation, and personalized learning recommendations
使用说明 (SKILL.md)

AdaptiveTest

Production-grade adaptive testing API. Uses Item Response Theory (IRT 2PL/3PL) with Computerized Adaptive Testing (CAT) to deliver precise ability estimates in fewer questions. Includes AI-powered question generation and personalized learning recommendations.

When to Use This Skill

Use AdaptiveTest when the user needs to:

  • Create or manage assessments and tests
  • Run adaptive testing sessions that select questions based on student ability
  • Generate assessment questions by topic, difficulty, or academic standard
  • Get personalized learning recommendations for students
  • Calibrate test items using IRT parameter estimation
  • Manage students, classes, and enrollments
  • Analyze test results and track student mastery

Authentication

All requests require the X-API-Key header:

X-API-Key: ${ADAPTIVETEST_API_KEY}

Base URL: https://adaptivetest-platform-production.up.railway.app/api

Core Workflows

1. Create and Administer an Adaptive Test

POST /tests              -- Create a test (set cat_enabled: true)
POST /tests/{id}/items   -- Add items to the test
POST /tests/{id}/sessions -- Start an adaptive session for a student
GET  /sessions/{id}/next-item -- Get the next CAT-selected item
POST /sessions/{id}/responses -- Submit student response
GET  /sessions/{id}/results   -- Get ability estimate and results

The CAT engine selects items using maximum Fisher information. Ability is estimated after each response using IRT 2PL or 3PL models. Sessions terminate when the standard error drops below threshold or max items are reached.

2. Generate Questions with AI

POST /gen-q -- Generate questions by topic, difficulty, and standard

Request body:

{
  "topic": "Quadratic equations",
  "difficulty": "medium",
  "count": 5,
  "standard": "CCSS.MATH.CONTENT.HSA.REI.B.4",
  "format": "multiple_choice"
}

Returns QTI 3.0-compatible items with stems, distractors, and rationales. Generation takes ~7 seconds.

3. Get Learning Recommendations

POST /recs -- Get personalized learning recommendations for a student

Request body:

{
  "student_id": "student-uuid",
  "subject": "Mathematics",
  "include_resources": true
}

Returns a personalized learning plan based on the student's ability profile and assessment history. Generation takes ~25 seconds.

4. Calibrate Test Items

POST /tests/{id}/calibrate -- Run IRT calibration on collected response data

Requires sufficient response data (minimum 30 responses per item recommended). Returns IRT parameters: difficulty (b), discrimination (a), and guessing (c) for 3PL.

5. Manage Students and Classes

POST /students           -- Create a student
GET  /students           -- List students
POST /classes            -- Create a class
POST /classes/{id}/enroll -- Enroll students in a class

OneRoster 1.2 compatible for SIS integration.

6. View Results and Analytics

GET /sessions/{id}/results       -- Detailed session results with ability estimate
GET /students/{id}/history       -- Assessment history for a student
GET /tests/{id}/analytics        -- Item-level analytics for a test

Rate Limits

Rate limits depend on your API key tier. Check X-RateLimit-Remaining header on each response.

Error Handling

All errors return JSON with a detail field:

{"detail": "Human-readable error message"}

Common status codes: 400 (validation), 401 (auth), 403 (limit exceeded), 404 (not found), 429 (rate limited).

Reference Documentation

For detailed endpoint specifications, request/response shapes, and IRT/CAT concepts, see the references/ directory:

  • references/api-endpoints.md -- Full endpoint reference
  • references/adaptive-testing.md -- IRT and CAT concepts
  • references/calibration.md -- Item calibration guide
安全使用建议
This skill appears coherent with its described purpose, but before installing consider: (1) only provide an API key from a trusted AdaptiveTest account and avoid using high-privilege or production keys when testing; (2) confirm the vendor, domain (the skill points to a Railway-hosted production URL), and data-handling promises (FERPA/PII protections, data residency, retention, and deletion policies) meet your legal/compliance needs; (3) test with non-sensitive or sandbox data first and monitor rate limits; (4) rotate keys regularly and scope them (least privilege) if the platform supports it; and (5) review the provider's SLA, pricing, and support/contact info (README/CLAUDE.md include a contact email). If any of these details are unclear from the vendor, ask for clarifying documentation before sending real student data.
功能分析
Type: OpenClaw Skill Name: adaptivetest-skill Version: 1.0.1 The skill bundle is primarily documentation and metadata (JSON, Markdown). It contains no executable code. The `SKILL.md` declares `curl` as a required binary and `ADAPTIVETEST_API_KEY` for authentication, which are standard for an API-interacting skill. All markdown files, including `SKILL.md` and `README.md`, are descriptive and instructional for using the AdaptiveTest API and do not contain any prompt injection attempts, instructions for malicious actions, or indicators of data exfiltration to unauthorized endpoints. The base URL `https://adaptivetest-platform-production.up.railway.app/api` is clearly specified and appears legitimate for the stated purpose.
能力评估
Purpose & Capability
Name/description map directly to the documented API endpoints and capabilities (IRT/CAT, question generation, recommendations). The only required artifact (ADAPTIVETEST_API_KEY) and required binary (curl) are appropriate for an HTTP API client.
Instruction Scope
SKILL.md contains only HTTP endpoint usage and API workflows that align with the stated purpose. It does not instruct reading local files, shell history, or unrelated environment variables, nor does it direct data to endpoints other than the documented base URL.
Install Mechanism
No install spec or downloaded code is present; this is an instruction-only skill that assumes an HTTP client (curl) is available. That minimizes code written to disk and reduces install-time risk.
Credentials
The skill requires a single API key (ADAPTIVETEST_API_KEY) to authenticate to the documented service. That is proportionate to an API-wrapping skill; no unrelated credentials or config paths are requested.
Persistence & Privilege
The skill is not configured as always-on and is user-invocable. It does not claim any ability to modify other skills or system-wide agent settings.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install adaptivetest-skill
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /adaptivetest-skill 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.1
Move internal specs to private repo to clarify credential boundaries
元数据
Slug adaptivetest-skill
版本 1.0.1
许可证
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Adaptivetest Skill 是什么?

Adaptive testing engine with IRT/CAT, AI question generation, and personalized learning recommendations. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 380 次。

如何安装 Adaptivetest Skill?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install adaptivetest-skill」即可一键安装,无需额外配置。

Adaptivetest Skill 是免费的吗?

是的,Adaptivetest Skill 完全免费(开源免费),可自由下载、安装和使用。

Adaptivetest Skill 支持哪些平台?

Adaptivetest Skill 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Adaptivetest Skill?

由 woodstocksoftware(@woodstocksoftware)开发并维护,当前版本 v1.0.1。

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