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format-for-audience
Adapts delivery content to the target audience's tone, detail level, and format expectations.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Adapts delivery content to the target audience's tone, detail level, and format expectations.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | format-for-audience |
| version | 1.0.0 |
| description | Adapts delivery content to the target audience's tone, detail level, and format expectations. |
| category | reporting |
| trigger | Before sharing any output externally. After generating a report, update, or assessment. |
| autonomy | autonomous |
| portability | universal |
| complexity | basic |
| type | generation |
| inputs | [{"name":"content","type":"text","required":true,"description":"The delivery content to reformat (report, update, assessment, memo)."},{"name":"audience","type":"text","required":true,"description":"Target audience: c-level, product, engineering-management, engineering-team, cross-team, or custom description."},{"name":"format","type":"text","required":false,"description":"Output format: markdown (default), team-chat, email, wiki, presentation-bullets."}] |
| outputs | [{"name":"formatted_content","type":"text","description":"Content reformatted for the specified audience and channel."}] |
| model_compatibility | ["claude","gpt-4","gemini","llama-3"] |
Adapt delivery management content for specific audiences and output channels. The same sprint data should read differently for a VP than for the engineering team.
| Audience | Tone | Detail Level | Focus | Avoid |
|---|---|---|---|---|
| C-Level / VP | Executive, confident, metrics-first | 3-5 bullets, 1 page max | RAG status, business impact, decisions needed, timeline | Ticket keys, technical jargon, process details |
| Product | Feature-oriented, outcome-focused | Per-feature status, 1-2 pages | Completion status, dates, scope changes, user impact | Infrastructure details, code-level issues |
| Engineering Management | Detailed, operational | Full report, 2-3 pages | Velocity, capacity, blockers, tech risks, process health | Business strategy, revenue metrics |
| Engineering Team | Direct, actionable, specific | Brief, 1 page | Sprint status, priority tickets, review queue, who needs help | High-level strategy, stakeholder politics |
| Cross-Team | Neutral, dependency-focused | 1 page | Shared blockers, integration points, timeline alignment | Team-internal details, individual performance |
If the audience is not in this table, ask for a brief description and apply the closest profile.
Apply these transformations based on the audience:
For C-Level / VP:
For Product:
For Engineering Management:
For Engineering Team:
For Cross-Team:
| Format | Constraints |
|---|---|
| Markdown | Headers, tables, bold for key metrics. Standard for detailed reports. |
| Team Chat (Slack, Teams, Discord) | Max 5 bullets per section. Bold with *text*. No tables (use aligned text). Thread-friendly. |
| Subject line + 3-5 paragraph structure. Professional greeting/closing. Key metrics in first paragraph. | |
| Wiki (Confluence, Notion, etc.) | Wiki-compatible markdown. Link ticket keys to tracker. Use info/warning panels for highlights. |
| Presentation bullets | One idea per bullet. Max 6 bullets per slide concept. No full sentences — fragments and metrics. |
After reformatting, verify:
The reformatted content, prefixed with a metadata line:
> Formatted for: {audience} | Channel: {format} | Source: {original output type}
{reformatted content}
Generates messages suggesting a ghost-done ticket be transitioned to Done. Helpful tone, evidence-based, always asks rather than commands.
Generates contextual, humble messages designed to unblock stuck tickets. Use when a stuck ticket needs a nudge comment.
Generates a quick morning briefing with what happened, what's stuck, and what needs attention today.
Evaluates whether epics are ready for PI or quarter planning by scoring 7 readiness dimensions.
Computes team capacity for a sprint or PI from headcount, PTO, and run-rate buffer.
Estimates completion probability for remaining work using velocity distribution and Monte Carlo-style simulation.