Crawl4AI Web Scraping
smallnest/goclaw
Scrapes sites, handles JavaScript-heavy pages and extracts structured data with Crawl4AI, through its crwl CLI or Python SDK, including schema-based extraction without an LLM.
Data pipeline design, ETL processes, Spring Integration patterns, batch processing for political data
$ npx skills add Hack23/cia --skill data-pipeline-engineering -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Hack23/cia data-pipeline-engineering --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/Hack23/cia.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/data-pipeline-engineering .claude/skills/data-pipeline-engineering && 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 "data-pipeline-engineering" agent skill from https://github.com/Hack23/cia/tree/master/.github/skills/data-pipeline-engineering into .claude/skills/data-pipeline-engineering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-pipeline-engineering", 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/Hack23/cia/tree/master/.github/skills/data-pipeline-engineeringType 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 Hack23/cia --skill data-pipeline-engineering -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Hack23/cia data-pipeline-engineering --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Hack23/cia.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.github/skills/data-pipeline-engineering .agents/skills/data-pipeline-engineering && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "data-pipeline-engineering" agent skill from https://github.com/Hack23/cia/tree/master/.github/skills/data-pipeline-engineering into .agents/skills/data-pipeline-engineering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-pipeline-engineering", 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 Hack23/cia --skill data-pipeline-engineering -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Hack23/cia data-pipeline-engineering --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Hack23/cia.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.github/skills/data-pipeline-engineering .cursor/skills/data-pipeline-engineering && 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 "data-pipeline-engineering" agent skill from https://github.com/Hack23/cia/tree/master/.github/skills/data-pipeline-engineering into .cursor/skills/data-pipeline-engineering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-pipeline-engineering", 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/Hack23/cia.git --path .github/skills/data-pipeline-engineering--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 Hack23/cia --skill data-pipeline-engineering -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Hack23/cia data-pipeline-engineering --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Hack23/cia.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.github/skills/data-pipeline-engineering .gemini/skills/data-pipeline-engineering && 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 "data-pipeline-engineering" agent skill from https://github.com/Hack23/cia/tree/master/.github/skills/data-pipeline-engineering into .gemini/skills/data-pipeline-engineering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-pipeline-engineering", 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 Hack23/cia data-pipeline-engineeringInstalls 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 Hack23/cia --skill data-pipeline-engineering -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Hack23/cia.git skills-src && mkdir -p .github/skills && cp -r skills-src/.github/skills/data-pipeline-engineering .github/skills/data-pipeline-engineering && 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 "data-pipeline-engineering" agent skill from https://github.com/Hack23/cia/tree/master/.github/skills/data-pipeline-engineering into .github/skills/data-pipeline-engineering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-pipeline-engineering", 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 Hack23/cia --skill data-pipeline-engineering -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Hack23/cia data-pipeline-engineering --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Hack23/cia.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.github/skills/data-pipeline-engineering .opencode/skills/data-pipeline-engineering && 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 "data-pipeline-engineering" agent skill from https://github.com/Hack23/cia/tree/master/.github/skills/data-pipeline-engineering into .opencode/skills/data-pipeline-engineering/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-pipeline-engineering", 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.
data-pipeline-engineeringData pipeline design, ETL processes, Spring Integration patterns, batch processing for political data
Data Pipeline Engineering is an agent skill from Hack23/cia. Data pipeline design, ETL processes, Spring Integration patterns, batch processing for political data
Its SKILL.md is about 1.9k 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 Data & Analytics, covering Data pipelines and ETL. The repository describes itself as: Citizen Intelligence Agency. Open-source intelligence platform analyzing Swedish political activities using AI and data visualization. Tracks politicians, government… The licence is Apache-2.0.
Read from SKILL.md and the folder at commit 6a9797b. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are java).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Data Pipeline Engineering loads about 1.9k tokens when it runs. Until then it costs about 32 tokens; SKILL.md has 234 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.
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.
The full file from Hack23/cia at commit 6a9797b, republished under its Apache-2.0 licence (© Hack23). 234 words, ~1,940 tokens.
.claude/skills/data-pipeline-engineering/SKILL.md (or your agent's skills folder).Design and implement robust data pipelines for the CIA platform that extract, transform, and load Swedish political data from multiple sources into the internal data model. Covers Spring Integration, batch processing, and monitoring patterns.
Do NOT use for:
┌────────────┐ ┌────────────┐ ┌────────────┐ ┌────────────┐
│ Extract │───▶│ Transform │───▶│ Load │───▶│ Monitor │
│ │ │ │ │ │ │ │
│ API Fetch │ │ Validate │ │ JPA Upsert │ │ Metrics │
│ XML/JSON │ │ Map Fields │ │ Batch Save │ │ Alerts │
│ Pagination │ │ Enrich │ │ Index │ │ Dashboards │
└────────────┘ └────────────┘ └────────────┘ └────────────┘@Configuration
public class RiksdagPipelineConfig {
@Bean
public IntegrationFlow riksdagImportFlow() {
return IntegrationFlow
.from(pollingSource(), e -> e.poller(
Pollers.cron("0 0 2 * * *") // Daily at 2 AM
.maxMessagesPerPoll(1)
.errorHandler(pipelineErrorHandler())))
.channel("riksdagRawChannel")
.transform(xmlToJsonTransformer())
.split(personListSplitter())
.channel(c -> c.executor(taskExecutor()))
.filter(dataQualityFilter())
.transform(entityMapper())
.aggregate(batchAggregator())
.handle(jpaOutboundAdapter())
.get();
}
@Bean
public TaskExecutor taskExecutor() {
ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
executor.setCorePoolSize(4);
executor.setMaxPoolSize(8);
executor.setQueueCapacity(1000);
executor.setThreadNamePrefix("riksdag-pipeline-");
return executor;
}
}@Bean
public IntegrationFlow errorFlow() {
return IntegrationFlow
.from("errorChannel")
.handle(message -> {
MessagingException exception = (MessagingException) message.getPayload();
LOG.error("Pipeline error: {}", exception.getMessage(), exception);
metricsService.incrementErrorCount("riksdag-pipeline");
// Route to dead letter queue for manual review
Message<?> failedMessage = exception.getFailedMessage();
deadLetterRepository.save(new DeadLetterEntry(
failedMessage.getPayload().toString(),
exception.getMessage(),
Instant.now()
));
})
.get();
}@Configuration
public class VoteImportBatchConfig {
@Bean
public Job voteImportJob(JobRepository jobRepository, Step importStep) {
return new JobBuilder("voteImportJob", jobRepository)
.incrementer(new RunIdIncrementer())
.start(importStep)
.build();
}
@Bean
public Step importStep(JobRepository jobRepository,
PlatformTransactionManager txManager) {
return new StepBuilder("importVotes", jobRepository)
.<RiksdagVote, VoteData>chunk(100, txManager)
.reader(voteReader())
.processor(voteProcessor())
.writer(voteWriter())
.faultTolerant()
.retryLimit(3)
.retry(TransientDataAccessException.class)
.skipLimit(10)
.skip(DataValidationException.class)
.listener(stepListener())
.build();
}
}| Data Type | Records/Batch | Chunk Size | Reason |
|---|---|---|---|
| Person data | ~350 | 50 | Small dataset, frequent updates |
| Vote records | ~100K/session | 500 | Large dataset, bulk insert |
| Documents | ~50K | 100 | Variable size, careful processing |
| Committee data | ~100 | 25 | Small, relational integrity |
@Component
public class RiksdagEntityMapper {
public PersonData mapPerson(RiksdagPerson source) {
PersonData target = new PersonData();
target.setId(source.getIntressentId());
target.setFirstName(sanitize(source.getFornamn()));
target.setLastName(sanitize(source.getEfternamn()));
target.setParty(normalizeParty(source.getParti()));
target.setBornYear(parseYear(source.getFoddAr()));
target.setGender(normalizeGender(source.getKon()));
target.setStatus(source.getStatus());
target.setImportTimestamp(Instant.now());
return target;
}
private String sanitize(String input) {
if (input == null) return null;
String trimmed = input.trim().replaceAll("[\\p{Cntrl}]", ""); // Remove control characters
return trimmed.substring(0, Math.min(trimmed.length(), 255));
}
private String normalizeParty(String party) {
return Optional.ofNullable(party)
.map(String::trim)
.map(String::toUpperCase)
.orElse("-");
}
}@Component
public class PipelineScheduler {
@Scheduled(cron = "0 0 2 * * *") // Daily full refresh
public void dailyFullImport() {
LOG.info("Starting daily full import");
importService.importAll();
}
@Scheduled(cron = "0 */15 8-18 * * MON-FRI") // Every 15 min during sessions
public void incrementalVoteImport() {
if (riksdagSessionActive()) {
LOG.info("Starting incremental vote import");
importService.importRecentVotes();
}
}
}@Component
public class PipelineMetrics {
private final MeterRegistry meterRegistry;
public void recordImport(String pipeline, int recordCount, long durationMs) {
meterRegistry.counter("pipeline.records.imported",
"pipeline", pipeline).increment(recordCount);
meterRegistry.timer("pipeline.duration",
"pipeline", pipeline).record(durationMs, TimeUnit.MILLISECONDS);
}
public void recordError(String pipeline, String errorType) {
meterRegistry.counter("pipeline.errors",
"pipeline", pipeline,
"error_type", errorType).increment();
}
}| Control | Requirement |
|---|---|
| ISO 27001 A.8.10 | Information deletion / data retention |
| ISO 27001 A.5.33 | Protection of records |
| NIST CSF PR.DS-1 | Data-at-rest protection |
| CIS Control 3 | Data protection |
© Hack23, 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
Just SKILL.md in .github/skills/data-pipeline-engineering of Hack23/cia.
Open the folder on GitHubat commit 6a9797b
Data Pipeline Engineering 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 |
|---|---|---|---|---|---|---|
| Data Pipeline Engineering this skillHack23/cia | 239 | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| Crawl4AI Web Scrapingsmallnest/goclaw | 598 | 1 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Glue 09 10 Migrationaws-samples/aws-glue-samples | 1.5k | — | ~2.4k | Automated safety check: Pass | MIT-0 | |
| Migrate Glue Devendpoint To Interactive Sessionsaws-samples/aws-glue-samples | 1.5k | — | ~3.6k | Automated safety check: Pass | MIT-0 | |
| Dbt Databricks PR Readydatabricks/dbt-databricks | 379 | — | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| Mz Dbt ReleaseMaterializeInc/materialize | 6.4k | — | ~1.2k | Automated safety check: Pass | Custom licence |
smallnest/goclaw
Scrapes sites, handles JavaScript-heavy pages and extracts structured data with Crawl4AI, through its crwl CLI or Python SDK, including schema-based extraction without an LLM.
aws-samples/aws-glue-samples
Upgrade an AWS Glue ETL job from Glue version 0.9 or 1.0 to Glue 4.0.
aws-samples/aws-glue-samples
Migrate a legacy AWS Glue development endpoint to a Glue interactive session, following the official AWS migration checklist.
databricks/dbt-databricks
A skill your agent uses for an open dbt-databricks pull request, including your own PR or a fork PR, to assess merge readiness and optionally repair selected gaps on the PR head branch.
MaterializeInc/materialize
Cut a dbt-materialize PyPI release: bump the version in version.py and setup.py, date the Unreleased CHANGELOG entry, and open the release PR with a Ship: <url body.
liam-machine/erd-studio
Friendly, step-by-step setup for ERD Studio in an existing dbt project, for people who may be new to dbt or data modelling.
Hack23/cia
WCAG 2.1 AA compliance, ARIA attributes, keyboard navigation, screen reader optimization for accessible political data platforms
Hack23/cia
Advanced chart types, D3.js/Vaadin Charts patterns, political data visualization, time series analysis
Hack23/cia
AI governance, EU AI Act compliance, OWASP LLM security, responsible AI practices for GitHub Copilot agents
Hack23/cia
External API integration patterns, retry logic, circuit breakers, caching, rate limiting for government data APIs
Hack23/cia
AWS CloudWatch metrics, alarms, dashboards, log insights, and application monitoring for the CIA platform
Hack23/cia
AWS security best practices, VPC security, IAM, KMS, CloudTrail, GuardDuty for CIA platform deployment
Categories
Data pipeline design, ETL processes, Spring Integration patterns, batch processing for political data. Data Pipeline Engineering is an agent skill from Hack23/cia.
Data Pipeline Engineering fits situations like: tasks that involve Data pipelines and ETL.
Run `npx skills add Hack23/cia --skill data-pipeline-engineering -a claude-code`. Or copy the skill folder (.github/skills/data-pipeline-engineering in Hack23/cia) into .claude/skills/data-pipeline-engineering in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Hack23/cia --skill data-pipeline-engineering -a codex`. Or copy the skill folder (.github/skills/data-pipeline-engineering in Hack23/cia) into .agents/skills/data-pipeline-engineering in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Hack23/cia --skill data-pipeline-engineering -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/data-pipeline-engineering, .gemini/skills/data-pipeline-engineering, .github/skills/data-pipeline-engineering and .opencode/skills/data-pipeline-engineering in your project.
SKILL.md names no scripts, command-line tools or credentials: Data Pipeline Engineering is instructions for the agent only.
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.
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.
Data Pipeline Engineering is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.9k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Data Pipeline Engineering: Crawl4AI Web Scraping (smallnest/goclaw, 598 stars), Glue 09 10 Migration (aws-samples/aws-glue-samples, 1.5k stars), Migrate Glue Devendpoint To Interactive Sessions (aws-samples/aws-glue-samples, 1.5k stars) and Dbt Databricks PR Ready (databricks/dbt-databricks, 379 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Hack23 (a GitHub organization) maintains it in Hack23/cia, which has 239 GitHub stars. The repository holds 78 skills in this directory. The repository was last updated on October 6, 2026.
Source: Hack23/cia on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.