gather-business-context

作者: openai

从已连接或提供的来源收集业务上下文,以便下游分析从正确的框架开始。在进行更深入的分析之前使用,当分析…

npx skills add https://github.com/openai/role-specific-plugins --skill gather-business-context

Boundary

Use this skill to gather framing context, not to complete the downstream analysis.

If the same request also asks for a diagnosis, recommendation, dashboard, report, or other analytical deliverable, return only the context needed for that next step and continue with the appropriate focused skill, such as $metric-diagnostics, $product-business-analysis, $build-dashboard, or $build-report.

Gather Business Context

Use this skill to collect the business context needed to understand an analytical question before doing deeper work. Focus on what the topic is, why it matters, what changed or is being decided, who or what source is closest to the work, and which definitions or artifacts should frame the analysis. This is a retrieval and extraction skill: gather enough context to set up the next step, not a final report, root-cause analysis, or broad background scan. Skip it when the prompt already provides the needed context or the task is fully self-contained.

Workflow

1. Identify The Retrieval Target

Establish the analytical topic that needs context and why it matters for the next step. Capture the boundary needed to search and interpret sources, such as the relevant product area, audience, time period, or decision. If the timeframe is missing, use the narrowest reasonable window implied by the task and label it as an assumption.

2. Build Search Anchors

Search with concrete identifiers rather than broad topic guesses. Start with the names the user provided or the sources surfaced, then expand with adjacent terms that help recall, such as aliases, owners, teams, dates, source names, related entities, or entities found in earlier results.

Start broad enough to avoid missing relevant context. If too much comes back and a quick scan suggests the results are mostly unrelated, combine anchors to narrow retrieval, for example a metric plus a dashboard name, a feature plus a launch window, or a customer plus the relevant workflow. If a likely source comes back thin, revise the anchors before treating the source as missing.

3. Search From Discovery Points Toward Authoritative Artifacts

  1. Explore all possible sources. Search every enabled or provided source family that could contain useful context or task-relevant data. Within each structured-data source, run fresh catalog or metadata discovery for relevant schemas, datasets, tables, views, models, and metrics. User-named sources, known tables, dashboards, and semantic-layer anchors are starting points, not stopping points.
  2. Compare duplicates and conflicts. When sources overlap or disagree, compare authority, freshness, definition, scope, and directness. Prefer artifacts closest to what was decided, defined, implemented, or measured; follow linked evidence when useful. Note material conflicts and explain which source or combination should guide downstream analysis.

4. Extract Only Decision-Shaping Context

Treat business context as a fixed extraction target, not an open-ended summary. Capture the facts that will shape the downstream analysis: the topic's business meaning, why it matters now, how it is defined or measured, where to verify it, what recently changed, and what uncertainty should travel with the analysis. Examples can include a metric definition, current rollout state, dashboard link, owner note, source conflict, or stated next step.

Keep the context note focused on details that help frame the next analysis. Skip broad background, adjacent history, or long source excerpts unless they add useful context.

5. Keep Source Notes Compact And Attributable

For each useful source, record enough attribution for the downstream work to be checked later: when the source applies, what kind of source it is, what factual context it established, and any important caveat or conflict. Distinguish source facts from inference and do not imply source review, stakeholder views, metric certainty, or confidence beyond what was actually established.

6. Reconcile Conflicts Explicitly

When sources disagree in a way that could change the downstream framing, preserve the disagreement instead of smoothing it over. Prefer the newest explicit decision artifact over older plans, owner-written docs over third-party summaries, and implementation artifacts over aspirational plans when the question is what is live, shipped, logged, or queryable now. Treat an informal source as stronger than a canonical artifact only when it clearly records a later decision or owner confirmation.

If disagreement remains, present both views, label the conflict, and state what source or owner would resolve it. If context is stale or incomplete, say what is missing and where to look next.

7. Stop Once The Framing Is Sound

Stop gathering context when the downstream task can be framed well enough to proceed and the likely enabled or provided source families have been checked, ruled out as unavailable, or identified as too thin. Before stopping, make sure the next step has a clear enough understanding of the topic, why it matters, where the important definitions came from, what recent context applies, and what gaps remain.

Continue searching when a relevant enabled or provided source is likely to add useful context. If an expected source was not found, name that as a gap rather than implying it does not exist.

8. Return A Lightweight Context Note When Useful

Prefer a focused context note over a full report or raw retrieval dump. Include enough context for the next analysis to proceed without redoing the search: a short summary, the relevant context, important definitions or source links, uncertainty or caveats, and citations. Keep it readable, but do not compress away details that explain the framing or source quality.

If the user asked only for quick orientation, shorten the structure while preserving citations, conflicts, and missing canonical artifacts.

Standards

Judge sources by what they can actually establish. Informal discussion can be useful for discovery and recent context, but durable artifacts are usually stronger evidence for definitions, decisions, status, and measured results once found. Prefer sources close to the work, recent enough to reflect current reality, and explicit about what they establish. Surface missing source-of-truth artifacts as context gaps.

Keep important claims attributable. Treat a source as useful only when it clarifies how the downstream task should be framed or interpreted; sources that merely mention the topic are incidental. Preserve enough evidence to check the work later, and label interpretation, assumptions, conflicts, and uncertainty when support is thin, stale, indirect, or conflicting.

Preserve disagreements that could change the framing. Prefer owner-authored or decision-adjacent material and evidence of what is current over secondhand summaries or speculation. Do not infer consensus from silence. Say what source or owner would resolve an important conflict.

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