cikm-reproducibility
Use when hardening the reproducibility of a CIKM paper — pinning the pipeline stages where IR, mining, and knowledge-management results silently diverge, documenting KGs and enterprise data that cannot be released, keeping the GenAI disclosure consistent with how code and data were produced, and preparing the post-acceptance release.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cikm-reproducibility --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# CIKM Reproducibility Reproducibility at CIKM has a venue-specific difficulty: the typical paper chains components from different communities — an index, a graph, a model, a ruleset — and each link has its own silent-divergence habits. A reader who cannot rebuild the chain cannot attribute the result, and a blended review panel contains someone able to notice each weak link. ## Divergence map for chained pipelines | Chain link | How results silently drift | Pin | |---|---|---| | Text preprocessing / indexing | Tokenizer versions, stopword lists, index-time defaults differ across toolkits | Name toolkit + version + config file in the artifact | | KG snapshot | Public KGs (Wikidata-class) change daily; entity counts drift | Freeze and state the dump date; ship the extracted subgraph if licensable | | Candidate generation | Recall stage caps and thresholds rarely reported | Report every cutoff; they bound the final metrics | | Training | Seeds, hardware nondeterminism, early-stopping criteria | Seed policy + selection rule in the protocol paragraph | | Evaluation | Metric implementations disagree at tie-breaking and cutoffs | Name the evaluation library version; never hand-roll silen
- Divergence map for chained pipelines
- Unreleasable data, releasable knowledge
- GenAI disclosure as a reproducibility document
- Environment capture
- Where reproducibility pays at this venue
- Release timeline
- Honest-failure disclosure
- One-command bar
- Output format
The replication target for a CIKM chained pipeline: git clone <repo> && cd <repo> make setup # pinned environment, data download or synthetic analog make table2 # rebuilds the headline table end-to-end from the frozen inputs
What does the cikm-reproducibility skill do?
Use when hardening the reproducibility of a CIKM paper — pinning the pipeline stages where IR, mining, and knowledge-management results silently diverge, documenting KGs and enterprise data that cannot be released, keeping the GenAI disclosure consistent with how code and data were produced, and preparing the post-acceptance release.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cikm-reproducibility --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.