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- notque/vexjoy-agent
- 최근 소스 활동
- 2026년 7월 5일 20:41
- 감지된 SKILL.md 언어
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설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/notque/vexjoy-agent --skill news-collection명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SKILL.md 표시 중
| name | news-collection |
| promoted_to | content-calendar |
| description | Collect, filter, and freshness-qualify news items. |
| user-invocable | false |
| routing | {"triggers":["news collection","collect news","qualify news items","news triage","filter news feed","check news freshness"],"not_for":"general research reports — that is research-pipeline. Pick this when the input is a stream of news items to qualify for a content pipeline.","pairs_with":["fact-check"],"complexity":"Medium","category":"research"} |
Gather news items on a topic, filter junk cheaply, verify freshness, and emit qualified items under an evidence contract. Pipeline-shaped: four phases, a gate between each. Content pipelines consume the JSON artifact; pair with fact-check to verify what this skill qualifies.
Goal: gather candidate items from available sources (feeds, search results, provided fixtures). Every item carries the five-fact evidence contract: title, url, outlet, author, published_at.
Rule (verbatim from the design): publish times are extracted (article
metadata), never guessed; missing timestamp → recorded as unknown, confidence
lowered and disclosed. A guessed timestamp poisons every downstream freshness
verdict; an honest "published_at": null keeps the item usable with known
uncertainty.
Record each item as one JSON object per the schema in
references/evidence-contract.md. Fill evidence_notes with where each fact
came from (meta tag, byline, JSON-LD, sitemap).
Distinguish outcomes: zero items because sources were unreachable is a collection failure (report it, stop); zero items from reachable sources is a valid empty feed (deliver an empty artifact with counts of zero).
Gate: every collected item has all five fields present — value or explicit
null with a confidence downgrade and a disclosure note. Items with silent
gaps stay in COLLECT until the gap is recorded.
Goal: cheap, high-recall pass over collected items. Three verdicts:
keep / monitor_only / reject, each with a reason code from
references/coarse-filter.md.
Rule (verbatim from the design): high-magnitude stories are downgraded to monitor_only at most, never rejected — a false keep is cheap, a silent drop is expensive. A keep costs one extra freshness check; a wrongly dropped major story costs the whole pipeline its value.
This phase runs on a cheap model when dispatched — it needs recall, not
judgment depth. See the dispatch note in references/coarse-filter.md.
Gate: every item has exactly one verdict and one reason code. reject
verdicts on items that look high-magnitude get re-checked once before the
phase closes.
Goal: for each keep and monitor_only item, establish when the story
first became public and whether this page is the original coverage. Methods in
references/freshness-forensics.md:
Rule (verbatim from the design): two independent sources or verdict "unclear". Conservative default: unclear over guessed. An "unclear" verdict is recoverable downstream; a confidently wrong "fresh" verdict ships stale news.
Gate: every surviving item carries freshness: fresh | stale | unclear, a
first_public_estimate (or null), and the count of sources backing the
verdict. Duplicate clusters are consolidated to one canonical item with
duplicates_of links.
Goal: emit qualified items as a structured JSON artifact (schema:
references/evidence-contract.md) plus a summary table. Every verdict state
appears in the artifact — monitor_only, unclear, and reject items ship
with their verdicts rather than vanishing, so consumers see the full triage.
Gate (deterministic phase checkpoint — emit this table before delivering the artifact; delivery without it is incomplete):
| Verdict | Count |
|---|---|
| keep | n |
| monitor_only | n |
| reject | n |
| unclear (freshness) | n |
| duplicates consolidated | n |
The counts make silent drops visible: collected total must equal keep + monitor_only + reject. If it does not, return to the phase that lost items.
No items collected
No timestamp found anywhere for an item
published_at: null, confidence: low, disclose in
evidence_notes; freshness verdict for that item is unclear.Two sources disagree on first-public time
references/freshness-forensics.md); if still split, verdict unclear.Item count mismatch at DELIVER
| Signal | Load These Files | Why |
|---|---|---|
| Recording items, JSON artifact schema, confidence fields | evidence-contract.md | Five-fact contract and artifact schema |
| Assigning verdicts, reason codes, cheap-model dispatch | coarse-filter.md | Verdict definitions and dispatch note |
| Dating a story, syndication, duplicates, canonical pick | freshness-forensics.md | Forensic methods and rubrics |
Run the full evidence-to-live implementation workflow for large, multi-system, multi-wave, or CPU-delegated 5 Star Booker GM programs.
Classify user requests and route to the correct agent + skill. Primary entry point for all delegated work.
Structured multi-phase workflows: review, debug, refactor (tidy, clean up, untangle messy code without behaviour change), deploy, create, research.
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