DeepTutor CLI
HKUDS/DeepTutor
Teaches the agent to set up and run DeepTutor from the command line: chat and capabilities, knowledge bases, partners, memory, sessions, notebooks and the server or Web app.
Independent multi-dimensional assessor for material design candidates.
Install Assessment Screening
$ npx skills add openJiuwen-ai/sciencediscovery --skill assessment-screening -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install openJiuwen-ai/sciencediscovery assessment-screening --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/openJiuwen-ai/sciencediscovery.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/assessment-screening .claude/skills/assessment-screening && rm -rf skills-srcUse ~/.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/
Install the "assessment-screening" agent skill from https://github.com/openJiuwen-ai/sciencediscovery/tree/main/skills/assessment-screening into .claude/skills/assessment-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assessment-screening", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/openJiuwen-ai/sciencediscovery/tree/main/skills/assessment-screeningType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add openJiuwen-ai/sciencediscovery --skill assessment-screening -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install openJiuwen-ai/sciencediscovery assessment-screening --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openJiuwen-ai/sciencediscovery.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/assessment-screening .agents/skills/assessment-screening && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "assessment-screening" agent skill from https://github.com/openJiuwen-ai/sciencediscovery/tree/main/skills/assessment-screening into .agents/skills/assessment-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assessment-screening", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add openJiuwen-ai/sciencediscovery --skill assessment-screening -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install openJiuwen-ai/sciencediscovery assessment-screening --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openJiuwen-ai/sciencediscovery.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/assessment-screening .cursor/skills/assessment-screening && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "assessment-screening" agent skill from https://github.com/openJiuwen-ai/sciencediscovery/tree/main/skills/assessment-screening into .cursor/skills/assessment-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assessment-screening", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/openJiuwen-ai/sciencediscovery.git --path skills/assessment-screening--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add openJiuwen-ai/sciencediscovery --skill assessment-screening -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install openJiuwen-ai/sciencediscovery assessment-screening --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openJiuwen-ai/sciencediscovery.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/assessment-screening .gemini/skills/assessment-screening && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "assessment-screening" agent skill from https://github.com/openJiuwen-ai/sciencediscovery/tree/main/skills/assessment-screening into .gemini/skills/assessment-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assessment-screening", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install openJiuwen-ai/sciencediscovery assessment-screeningInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add openJiuwen-ai/sciencediscovery --skill assessment-screening -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/openJiuwen-ai/sciencediscovery.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/assessment-screening .github/skills/assessment-screening && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "assessment-screening" agent skill from https://github.com/openJiuwen-ai/sciencediscovery/tree/main/skills/assessment-screening into .github/skills/assessment-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assessment-screening", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add openJiuwen-ai/sciencediscovery --skill assessment-screening -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install openJiuwen-ai/sciencediscovery assessment-screening --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openJiuwen-ai/sciencediscovery.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/assessment-screening .opencode/skills/assessment-screening && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "assessment-screening" agent skill from https://github.com/openJiuwen-ai/sciencediscovery/tree/main/skills/assessment-screening into .opencode/skills/assessment-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assessment-screening", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
assessment-screening- GitHub stars
- 159
- Token cost
- ~1.2k tokens
- SKILL.md length
- 389 words
- Files
- 4 (incl. references)
- Skills in repo
- 23
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Independent multi-dimensional assessor for material design candidates.
- Works in 4 steps: Real evaluation only — Provide genuine… → No fabricated data — Do not fabricate… → Independent assessment — Each dispatch… → …
- Tasks that involve Quizzes and assessments
- SKILL.md covers Role in the Workflow, When to Use, Do NOT Use For and Rubric Loading, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Assessment Screening is an agent skill from openJiuwen-ai/sciencediscovery. Independent multi-dimensional assessor for material design candidates. Loads configurable scoring rubrics to evaluate candidates from different expert perspectives. Each dispatch produces structured scores, pros/cons, and verification data without sharing results with other assessors.
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/rubric-agent-a.md`, `references/rubric-agent-b.md` and `references/rubric-agent-c.md`).
It sits in Education, covering Quizzes and assessments. The repository describes itself as: ScienceDiscovery is an all‑in‑one agentic workbench built specifically for scientific research. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Quizzes and assessments
Example prompts
- “/assessment-screening”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Real evaluation only — Provide genuine assessments based on available data, not fabricated scores.
- No fabricated data — Do not fabricate tool results, database identifiers, MP-IDs, CAS numbers, or any other identifiers.
- Independent assessment — Each dispatch is fully independent. Do not reference or attempt to align with other assessors' results.
- Failure reporting — If verification data is unavailable, explicitly state this and explain the implications for the score.
What it can do on your machine
Read from SKILL.md and the folder at commit ab1403f. 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
No scripts in the folder and no shell commands in SKILL.md (its code samples are json).
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
Assessment Screening loads about 1.2k tokens when it runs, and up to ~2.8k if it reads all its reference files. Until then it costs about 77 tokens; SKILL.md has 389 words of instructions outside code blocks.
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); files beside SKILL.md are not scanned.
SKILL.md
The full file from openJiuwen-ai/sciencediscovery at commit ab1403f, republished under its Apache-2.0 licence (© openJiuwen-ai). 389 words, ~1,178 tokens.
Download SKILL.mdSave it as
.claude/skills/assessment-screening/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- assessment-screening
- description
- Independent multi-dimensional assessor for material design candidates. Loads configurable scoring rubrics to evaluate candidates from different expert perspectives. Each dispatch produces structured scores, pros/cons, and verification data without sharing results with other assessors.
Assessment Screening
Evaluate material design candidates against configurable multi-dimensional scoring rubrics. Each dispatch operates as an independent expert: no shared scores, reasoning, or outputs between assessors.
Role in the Workflow
Dispatched by the Lead agent during leaf execution (Step 4.2 of the Idea Tree workflow). The Lead may dispatch multiple independent instances, each loading a different rubric perspective:
Lead agent
├── dispatches: assessment-screener (rubric: agent-a) → independent scores
├── dispatches: assessment-screener (rubric: agent-b) → independent scores
├── dispatches: assessment-screener (rubric: agent-c) → independent scores
└── dispatches: insight-aggregator (cross-validate & synthesize)When to Use
- The Lead agent has checkpointed a candidate material design artifact and needs independent multi-dimensional scoring.
- The dispatch context specifies which rubric perspective to load (
agent-a,agent-b,agent-c, oroverall).
Do NOT Use For
- Generating material designs (that is
creative-material-design's job). - Synthesizing insights or cross-validating other assessors (that is
insight-aggregator's job). - Literature search, evidence extraction, or report writing.
Rubric Loading
The assessor loads one rubric per dispatch based on the assessment_perspective field in the dispatch context:
| Perspective | Role | Reference File | Focus |
|---|---|---|---|
agent-a | activity | references/rubric-agent-a.md | Catalytic activity and reaction mechanism (weight 35%) |
agent-b | stability | references/rubric-agent-b.md | Structural stability and durability (weight 35%) |
agent-c | sustainability | references/rubric-agent-c.md | Environmental safety and sustainability (weight 30%) |
overall | — | references/rubric-overall.md | Cross-validation and final ranking (used by aggregator) |
If no perspective is specified, default to agent-a.
Scoring Model
Each assessor evaluates 4 role-specific dimensions and produces an overall_score (1-10). The server computes the final weighted score:
final_score = 0.35 × activity_overall + 0.35 × stability_overall + 0.30 × sustainability_overallEach assessor's dimensions are different (not shared):
| Role (Expert) | Dimensions |
|---|---|
| activity (A) | catalytic_activity, reaction_mechanism, selectivity, efficiency |
| stability (B) | structural_stability, durability, recyclability, lifetime |
| sustainability (C) | environmental_safety, sustainability, disposal, lifecycle |
Show full SKILL.md (155 more words)Show less
Critical Rules
- Real evaluation only — Provide genuine assessments based on available data, not fabricated scores.
- No fabricated data — Do not fabricate tool results, database identifiers, MP-IDs, CAS numbers, or any other identifiers.
- Independent assessment — Each dispatch is fully independent. Do not reference or attempt to align with other assessors' results.
- Failure reporting — If verification data is unavailable, explicitly state this and explain the implications for the score.
Output Format
{
"expert": "A",
"focus_area": "catalytic_activity_and_reaction_mechanism",
"snapshot_hash": "<candidate snapshot_hash>",
"candidate_version_id": "<exact checkpointed version>",
"evaluation": {
"<dimension_key>": {
"score": 1-10,
"analysis": "detailed analysis"
}
},
"overall_score": 1-10,
"recommendations": ["suggestion1", "suggestion2"],
"conclusion": "comprehensive assessment conclusion"
}Methodology
MUST read the loaded rubric reference file in full before scoring.
- Identify material — Classify the material type from the candidate artifact.
- Verify data — Cross-check claimed properties against available sources. Do not fabricate missing data; explain gaps.
- Score each dimension — Apply the rubric's 1-10 scale strictly. Do not assign scores that contradict the criteria.
- Generate feedback — Provide specific, actionable improvement suggestions.
- Produce output — Return the JSON structure above with exact
snapshot_hashandcandidate_version_idfrom the checkpointed artifact.
© openJiuwen-ai, Apache-2.0. 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 3 other files (references) in skills/assessment-screening of openJiuwen-ai/sciencediscovery.
- SKILL.md
- references/rubric-agent-a.md
- references/rubric-agent-b.md
- references/rubric-agent-c.md
Open the folder on GitHubat commit ab1403f
Compare with similar skills
Assessment Screening 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Assessment Screening this skillopenJiuwen-ai/sciencediscovery | 159 | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| DeepTutor CLIHKUDS/DeepTutor | 41k | — | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| AI Engineering Placement Quizrohitg00/ai-engineering-from-scratch | 67k | — | ~2k | Automated safety check: Pass | MIT | |
| Codebase to Coursezarazhangrui/codebase-to-course | 5.7k | — | ~4.4k | Automated safety check: Pass | None | |
| AI Engineering Phase Quizrohitg00/ai-engineering-from-scratch | 67k | — | ~2.1k | Automated safety check: Pass | MIT | |
| Scholar EvaluationK-Dense-AI/claude-scientific-writer | 2.4k | 2 repos | ~2.9k | Automated safety check: Notes | MIT |
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Related
Categories
Questions about Assessment Screening
What does Assessment Screening do?
Independent multi-dimensional assessor for material design candidates. Assessment Screening is an agent skill from openJiuwen-ai/sciencediscovery. Independent multi-dimensional assessor for material design candidates.
When should I use Assessment Screening?
Assessment Screening fits situations like: tasks that involve Quizzes and assessments.
How do I install Assessment Screening in Claude Code?
Run `npx skills add openJiuwen-ai/sciencediscovery --skill assessment-screening -a claude-code`. Or copy the skill folder (skills/assessment-screening in openJiuwen-ai/sciencediscovery) into .claude/skills/assessment-screening in your project. Claude Code loads it when a task matches its description.
How do I install Assessment Screening in Codex?
Run `npx skills add openJiuwen-ai/sciencediscovery --skill assessment-screening -a codex`. Or copy the skill folder (skills/assessment-screening in openJiuwen-ai/sciencediscovery) into .agents/skills/assessment-screening in your project. Codex loads it when a task matches its description.
Can I use Assessment Screening 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 openJiuwen-ai/sciencediscovery --skill assessment-screening -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/assessment-screening, .gemini/skills/assessment-screening, .github/skills/assessment-screening and .opencode/skills/assessment-screening in your project.
What does Assessment Screening need to run?
SKILL.md names no scripts, command-line tools or credentials: Assessment Screening is instructions for the agent only.
Does Assessment Screening 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 Assessment Screening 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. Review the folder before installing.
What licence does Assessment Screening use?
Assessment Screening is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Assessment Screening use?
About 1.2k tokens (SKILL.md is roughly 4.7k 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 1.6k tokens, read only when the agent opens those files.
What are the alternatives to Assessment Screening?
Skills that share tags, products or a category with Assessment Screening: DeepTutor CLI (HKUDS/DeepTutor, 41k stars), AI Engineering Placement Quiz (rohitg00/ai-engineering-from-scratch, 67k stars), Codebase to Course (zarazhangrui/codebase-to-course, 5.7k stars) and AI Engineering Phase Quiz (rohitg00/ai-engineering-from-scratch, 67k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Assessment Screening?
openJiuwen-ai (a GitHub organization) maintains it in openJiuwen-ai/sciencediscovery, which has 159 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on October 10, 2026.
Source: openJiuwen-ai/sciencediscovery on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.