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Agent skill
Cikm Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging the code, datasets, knowledge graphs, prompts, and demo systems around a CIKM paper — choosing the artifact form per track (research, applied, resource, demo)…
Install Cikm Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cikm-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cikm-artifact-evaluation --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/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/CIKM-Skills/skills/cikm-artifact-evaluation .claude/skills/cikm-artifact-evaluation && 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 "cikm-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CIKM-Skills/skills/cikm-artifact-evaluation into .claude/skills/cikm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cikm-artifact-evaluation", 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/brycewang-stanford/Awesome-Journal-Skills/tree/main/CIKM-Skills/skills/cikm-artifact-evaluationType 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 brycewang-stanford/Awesome-Journal-Skills --skill cikm-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cikm-artifact-evaluation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/CIKM-Skills/skills/cikm-artifact-evaluation .agents/skills/cikm-artifact-evaluation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "cikm-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CIKM-Skills/skills/cikm-artifact-evaluation into .agents/skills/cikm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cikm-artifact-evaluation", 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 brycewang-stanford/Awesome-Journal-Skills --skill cikm-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cikm-artifact-evaluation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/CIKM-Skills/skills/cikm-artifact-evaluation .cursor/skills/cikm-artifact-evaluation && 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 "cikm-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CIKM-Skills/skills/cikm-artifact-evaluation into .cursor/skills/cikm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cikm-artifact-evaluation", 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/brycewang-stanford/Awesome-Journal-Skills.git --path CIKM-Skills/skills/cikm-artifact-evaluation--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 brycewang-stanford/Awesome-Journal-Skills --skill cikm-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cikm-artifact-evaluation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/CIKM-Skills/skills/cikm-artifact-evaluation .gemini/skills/cikm-artifact-evaluation && 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 "cikm-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CIKM-Skills/skills/cikm-artifact-evaluation into .gemini/skills/cikm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cikm-artifact-evaluation", 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 brycewang-stanford/Awesome-Journal-Skills cikm-artifact-evaluationInstalls 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 brycewang-stanford/Awesome-Journal-Skills --skill cikm-artifact-evaluation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/CIKM-Skills/skills/cikm-artifact-evaluation .github/skills/cikm-artifact-evaluation && 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 "cikm-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CIKM-Skills/skills/cikm-artifact-evaluation into .github/skills/cikm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cikm-artifact-evaluation", 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 brycewang-stanford/Awesome-Journal-Skills --skill cikm-artifact-evaluation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cikm-artifact-evaluation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/CIKM-Skills/skills/cikm-artifact-evaluation .opencode/skills/cikm-artifact-evaluation && 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 "cikm-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CIKM-Skills/skills/cikm-artifact-evaluation into .opencode/skills/cikm-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cikm-artifact-evaluation", 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
cikm-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 724 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when packaging the code, datasets, knowledge graphs, prompts, and demo systems around a CIKM paper — choosing the artifact form per track (research, applied, resource, demo)…
- Packaging the code
- SKILL.md covers Artifact role by track, Resource-track packaging bar, KG-specific packaging and Demo systems as artifacts, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Knowledge graphs
What it does
Cikm Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging the code, datasets, knowledge graphs, prompts, and demo systems around a CIKM paper — choosing the artifact form per track (research, applied, resource, demo), meeting the resource track's reuse-and-documentation bar, and staging anonymous review artifacts into citable public releases.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Knowledge Management, covering Knowledge graphs. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- Packaging the code
- Knowledge graphs
- Demo systems around a CIKM paper — choosing the artifact form per track (research
- Meeting the resource tracks reuse-and-documentation bar
Example prompts
- “/cikm-artifact-evaluation”
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. 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.
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
Cikm Artifact Evaluation loads about 1.6k tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 724 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 brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 724 words, ~1,620 tokens.
Download SKILL.mdSave it as
.claude/skills/cikm-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- cikm-artifact-evaluation
- description
- Use when packaging the code, datasets, knowledge graphs, prompts, and demo systems around a CIKM paper — choosing the artifact form per track (research, applied, resource, demo), meeting the resource track's reuse-and-documentation bar, and staging anonymous review artifacts into citable public releases.
CIKM Artifact Evaluation
CIKM has no verified badge-granting artifact track (2026 lineup: full, short, applied, resource, demo — source map, 2026-07-08), but artifacts do more work here than at most venues, because two of the five tracks are about artifacts: Resource papers publish them, and Demonstration papers perform them. This skill covers the artifact strategy per track and the staging from anonymous review object to public citable release.
Artifact role by track
| Track | The artifact is... | Bar it must clear |
|---|---|---|
| Full / Short Research | Supporting evidence, cited anonymously | Regenerates headline results; survives a ten-minute inspection |
| Applied Research | Proof of practice | Substantiates the launch/deployment claim the track requires |
| Resource | The contribution itself | Documented, licensed, maintained, adoptable by strangers |
| Demonstration | The thing being demonstrated | Runs live, in front of people, on conference-venue conditions |
Resource-track packaging bar
A CIKM resource paper is graded on whether others will build on the object. The verified call names data resources, software, evaluation tasks, and open-source frameworks. Package accordingly:
- Provenance and license first: where the data came from, what consent/terms cover it, and a license a university lab and a company can both act on. An unlicensed dataset is unadoptable regardless of quality.
- Schema and statistics: field-level documentation, size, class balance, known gaps — the datasheet discipline, applied without the buzzword.
- Baselines included: a resource ships with reference numbers and the scripts that produce them, or every adopter re-invents the evaluation differently.
- Maintenance posture: versioning scheme, issue channel, and an honest statement of how long the hosting is funded. Reviewers of resource papers have watched too many datasets rot at dead URLs.
- All of it inside 4 pages (2026) — the paper is the resource's brochure and datasheet condensed; depth lives in the repository.
KG-specific packaging
Knowledge graphs — a CIKM staple — need artifact fields other objects skip: the dump date of any upstream KG, the extraction queries or rules that produced the subgraph, entity-resolution decisions (what merged, what split), and per-relation counts. Two teams "using Wikidata" are usually using different graphs; the artifact is where that ambiguity dies.
Demo systems as artifacts
A demo paper's artifact must run where demos actually happen: conference Wi-Fi, projector resolution, a visitor who types adversarial queries. Package a local fallback (cached index, canned dataset, offline model), a 90-second scripted tour, and a reset mechanism that restores clean state between visitors. The 4-page paper should include the architecture and what a visitor experiences — reviewers accept demos they can imagine standing in front of.
Show full SKILL.md (317 more words)Show less
Licensing quick guide
License choice is an adoption decision, and CIKM's mixed academic/industry audience makes it consequential:
| Object | Workable defaults | Watch out for |
|---|---|---|
| Code | MIT/Apache-2.0 for maximum reuse | Copyleft blocks industrial adopters — choose deliberately, not accidentally |
| Original data | CC BY (attribution) or CC BY-NC | NC clauses exclude exactly the applied audience CIKM attracts |
| Derived data (from a KG, a crawl, an API) | Whatever the upstream terms force | Upstream terms propagate: a Wikidata extraction, a scraped corpus, and an API dump each carry different obligations |
| Models/checkpoints | Code license or a stated model license | Base-model license inheritance for fine-tuned checkpoints |
Two failure modes recur in resource-track reviews: no license at all (unadoptable), and a license the authors had no right to grant because upstream terms forbid redistribution. Resolve the rights question before the paper claims release.
Hosting for the decade, not the deadline
CIKM papers become baselines years later (cikm-reproducibility), so host on that
horizon: an institutional or platform repository under an organization account
rather than a personal one; an archival deposit with a DOI for the exact
proceedings-version snapshot; dataset hosting with a stated funding horizon rather
than a lab NAS URL. The cheapest insurance is the archival snapshot — it survives
graduations, lab moves, and platform pivots, all of which the venue's older
artifact links have visibly failed to.
Anonymous-to-public staging
Review stage: anonymized hosting, no author-resolving URLs/metadata,
referenced from the PDF where each claim needs it
Acceptance: real repository public by camera-ready (13-day window in 2026 —
prepare during the review wait)
Public stage: license chosen; versioned release tagged to the proceedings
numbers; archival DOI (e.g., a Zenodo-class deposit) so citation
outlives the hosting; README linking the ACM DL recordThe GenAI Usage Disclosure obligation follows the artifact too: generated code,
synthetic data, or AI-produced labels inside the package belong in the paper's
disclosure section (cikm-reproducibility).
Naming and versioning conventions
Give the artifact the paper's short name (the mechanism name from
cikm-writing-style), version it semantically with the proceedings snapshot
tagged (e.g., v1.0-cikm2026), and keep the README's first line identical to the
paper title so search engines and readers connect the two objects. Post-
publication improvements go in later versions with a changelog; the tagged
snapshot stays frozen because it is what the paper's numbers mean.
Output format
[Track role] evidence / proof-of-practice / the-contribution / the-performance
[Package state] provenance / license / docs / baselines / maintenance
[KG fields] dump date / extraction / resolution decisions (if applicable)
[Staging] review-anonymous → public-citable, with dates
[Adoption blocker] <the single thing most likely to stop a stranger from using it>© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in CIKM-Skills/skills/cikm-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Cikm Artifact Evaluation 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 |
|---|---|---|---|---|---|---|
| Cikm Artifact Evaluation this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Obsidian Canvas BoardsAgriciDaniel/claude-obsidian | 15k | — | ~1.4k | Automated safety check: Pass | MIT | |
| Ontology1mancompany/OneManCompany | 442 | 2 repos | ~1.5k | Automated safety check: Pass | Apache-2.0 | |
| Knowledge Graphgnomeria/usbtree | 691 | — | ~1.5k | Automated safety check: Pass | MIT | |
| Graphagenticnotetaking/arscontexta | 3.5k | — | ~4.9k | Automated safety check: Notes | MIT | |
| LLM Wiki Knowledge GraphEgonex-AI/Understand-Anything | 86k | — | ~1.5k | Automated safety check: Pass | MIT |
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Typed knowledge graph for structured agent memory and composable skills.
Knowledge Graph
gnomeria/usbtree
Set up and maintain a lightweight, file-based knowledge graph of the repo — entities, typed relations, decisions, gotchas — so agents load context fast instead of re-exploring the codebase every…
Graph
agenticnotetaking/arscontexta
Interactive knowledge graph analysis. An agent skill from agenticnotetaking/arscontexta.
LLM Wiki Knowledge Graph
Egonex-AI/Understand-Anything
Detects a Karpathy-pattern LLM wiki and builds an interactive knowledge graph with entities, implicit relationships and topic clusters.
- Official
Gitnexus Guide
aws-samples/sample-kolya-br-proxy
A skill your agent uses when the user asks about GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference.
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Categories
Questions about Cikm Artifact Evaluation
What does Cikm Artifact Evaluation do?
A skill your agent uses when packaging the code, datasets, knowledge graphs, prompts, and demo systems around a CIKM paper — choosing the artifact form per track (research, applied, resource, demo)…. Cikm Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging the code, datasets, knowledge graphs, prompts, and demo systems around a CIKM paper — choosing the artifact form per track (research, applied, resource, demo), meeting the resource track's reuse-and-documentation bar, and staging anonymous review artifacts into citable public releases.
When should I use Cikm Artifact Evaluation?
Cikm Artifact Evaluation fits situations like: packaging the code; knowledge graphs; demo systems around a CIKM paper — choosing the artifact form per track (research; meeting the resource tracks reuse-and-documentation bar.
How do I install Cikm Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cikm-artifact-evaluation -a claude-code`. Or copy the skill folder (CIKM-Skills/skills/cikm-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/cikm-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Cikm Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cikm-artifact-evaluation -a codex`. Or copy the skill folder (CIKM-Skills/skills/cikm-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/cikm-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Cikm Artifact Evaluation 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 brycewang-stanford/Awesome-Journal-Skills --skill cikm-artifact-evaluation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cikm-artifact-evaluation, .gemini/skills/cikm-artifact-evaluation, .github/skills/cikm-artifact-evaluation and .opencode/skills/cikm-artifact-evaluation in your project.
What does Cikm Artifact Evaluation need to run?
SKILL.md names no scripts, command-line tools or credentials: Cikm Artifact Evaluation is instructions for the agent only.
Does Cikm Artifact Evaluation 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 Cikm Artifact Evaluation 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 Cikm Artifact Evaluation use?
Cikm Artifact Evaluation 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 Cikm Artifact Evaluation use?
About 1.6k tokens (SKILL.md is roughly 6.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Cikm Artifact Evaluation?
Skills that share tags, products or a category with Cikm Artifact Evaluation: Obsidian Canvas Boards (AgriciDaniel/claude-obsidian, 15k stars), Ontology (1mancompany/OneManCompany, 442 stars), Knowledge Graph (gnomeria/usbtree, 691 stars) and Graph (agenticnotetaking/arscontexta, 3.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Cikm Artifact Evaluation?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.