Bigdata Catalyst Monitor

作者 Bigdata-com2a52a0013662無授權條款2 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫昨天更新

Map the dated events that could move a public company over the next few quarters, using Bigdata.com data (events calendar, filings, news, tearsheet). Covers scheduled catalysts — earnings, investor days, index reviews, lock-up and patent expiries, regulatory decision dates — and foreseeable unscheduled ones — litigation milestones, product cycles, contract renewals, refinancings. Each catalyst carries a date or window, likely direction, magnitude, confidence, and what to watch, ranked by expected impact rather than by date alone. Triggers: "catalyst monitor for X", "what's coming up for X", "upcoming catalysts for X", "what could move X", "key dates for X", "event calendar for X", "what should I watch on X".

AI 產生的概覽

為上市公司建立未來可能影響股價的有日期事件行事曆,並依預期影響排序。

功能
使用 Bigdata.com 外掛工具為上市公司產出前瞻性催化劑行事曆。它會解析公司身分,取得已排定的財報與會議日期,擷取基準預估值與估值倍數,並針對可確定日期的事件進行定向搜尋,例如監管決定、訴訟節點、產品週期、合約續約、再融資、專利到期與指數審查。每項催化劑依日期或時間區間、類型、可能方向、影響幅度、信心程度及觀察重點評分,再依預期影響排序,並另附時間順序清單。輸出依報告範本,預設為 Markdown,可另提供 Word 或簡報版本。
適用情境
當問題關注公司接下來會發生什麼,而非過去已發生什麼時使用。適用於查詢即將到來的催化劑、關鍵日期、事件行事曆,或未來幾季可能推動股價的因素。不適用於回顧期摘要、深度財報前瞻、機率加權情境分析,或沒有解決日期的長期風險。
執行需求
需要存取 Bigdata.com 外掛工具:find_securities、bigdata_events_calendar、bigdata_company_tearsheet 與 bigdata_search,且除 search 與 fetch 外每次呼叫都需將 plugin_slug 設為該技能名稱。不附帶指令碼,僅為說明文件,另含報告範本與參考檔案。

Bigdata Catalyst Monitor

Forward calendar of what could move the name, ranked by impact. Use Bigdata.com plugin tools for every fact.

Use this skill when the question is "what's coming". Not this skill when:

RequestUse instead
What already happened over the past monthCompany brief
Deep analysis of the next earnings printEarnings preview
Probability-weighted outcomes and valuesScenario analysis
Risks rated by likelihood and impactRisk assessment

Catalyst vs risk: a catalyst is a dated or datable event that resolves something. A standing risk with no resolution date belongs in a risk assessment.

Data foundation (plugin tools)

ToolPurposePrerequisite
find_securitiesResolve company name → RavenPack entity_idNone
bigdata_events_calendarScheduled earnings and conferencesfind_securities
bigdata_company_tearsheetBaseline financials, estimates, what the price embedsfind_securities
bigdata_searchRegulatory dates, litigation milestones, product cycles, filingsNone

Required on every call: pass plugin_slug: "bigdata-catalyst-monitor" in the request parameters of every Bigdata.com plugin tool call made while running this skill. The value is always the skill name, bigdata-catalyst-monitor, regardless of the company or query.

Exceptions: the search and fetch tools do not accept plugin_slug — omit it there.

If the company name is ambiguous after find_securities, ask:

"I found multiple companies named [X]. Did you mean [Company A] in [Industry] or [Company B] in [Industry]?"

Workflow

Step 1 — Identify the company

Call find_securities with the company name to get the entity_id.

Step 2 — Scheduled events

Call bigdata_events_calendar for earnings dates and conferences over the next 2–4 quarters. Note the fiscal calendar so quarter-ends and guidance updates land correctly.

Step 3 — Baseline: what is already priced

Call bigdata_company_tearsheet. A catalyst only matters relative to expectations — capture consensus estimates, current multiples, and sentiment so each catalyst can be framed against what the market already assumes.

Step 4 — Search for datable events

Run 6–8 targeted searches:

  • "[Company] upcoming product launch roadmap timeline"
  • "[Company] regulatory decision approval date FDA / FTC / EU"
  • "[Company] lawsuit trial date court ruling expected"
  • "[Company] investor day capital markets day guidance update"
  • "[Company] contract renewal expiry major customer"
  • "[Company] debt maturity refinancing schedule"
  • "[Company] patent expiry exclusivity loss"
  • "[Company] index inclusion review lock-up expiry"

Include the industry-specific ones that apply — clinical readouts, license renewals, rate cases, spectrum auctions, model launches.

Step 5 — Rate each catalyst

For every catalyst record:

  • Date or window — exact where known, quarter where not; mark undated but expected items as such
  • Type — scheduled or foreseeable
  • Likely direction — positive / negative / two-sided
  • Magnitude — high / medium / low, tied to a value driver where possible ("~$Nm revenue", "~Xbps margin", "removes overhang on segment Y")
  • Confidence — how sure the date and the outcome are; these are different, and both matter
  • What to watch — the specific signal that tells you which way it resolved

Step 6 — Rank and sequence

Rank by expected impact, not chronology — a large two-sided event in nine months usually matters more than a routine print next week. Then give the chronological calendar separately, so the reader gets both views.

Close with the 2–3 catalysts that dominate the next few quarters and what each would change.

Output

Follow assets/report-template.md exactly — section order, tables, sources, and footer.

  • Add inline citations [1], [2] immediately after claims, hyperlinked to the document URL.
  • Every deliverable ends with the Powered by Bigdata.com line and the Disclaimer, verbatim.
  • Default format is Markdown; offer a Word (.docx) or presentation version if useful.

Quality bar

Non-negotiables:

  • Every catalyst carries a date or window — undated speculation is not a catalyst
  • Direction, magnitude, and confidence given separately; date confidence distinguished from outcome confidence
  • Magnitude tied to a value driver, not just labelled "high"
  • Ranked by impact and listed chronologically
  • Standing risks with no resolution date excluded — they belong in a risk assessment
  • Facts separated from analysis and implications

來源與署名

來源:Bigdata-com/bigdata-plugins-marketplace位於plugins/bigdata-com/skills/bigdata-catalyst-monitor提交2a52a00

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