AI Assistant Prompt Library — Collaboration Tasks
A categorized set of reusable prompt patterns, agent handoffs, and guardrails for common collaboration tasks: meeting summaries to actions, drafting, research framing, and facilitation support.
Purpose
This prompt library provides ready-to-use, shareable patterns for common collaboration tasks so teams can get consistent, reliable, and safe AI outputs. Each pattern includes expected inputs, desired outputs, and safety or attribution checks you should run before sharing results. Use these prompts as starting points — adapt wording and context to your team's voice, policies, and information sources.
How to use this library
- Provide clear context: give the assistant who, what, when, why, and any constraints.
- Specify the output format (bullet list, table, action list with owners, email draft, etc.).
- Include source constraints for research/prompts (e.g., internal docs only, cite URLs, date ranges).
- Run safety checks: ask the model to flag uncertainty, request citations, and highlight assumptions.
Categories & Prompt Patterns
Summaries — meeting notes to action lists
Use these when you need concise, actionable outcomes from a meeting transcript or notes.
Inputs: meeting notes or transcript; meeting date; attendee list; priority tags (optional).
Instruction (to assistant): "Read the meeting notes below. Produce a concise summary (2–4 sentences), then an ordered list of action items. For each action include: task, owner (if inferred), due date (if mentioned), priority (high/medium/low), and one-sentence context. If an item is ambiguous, label it 'Needs clarification' and list the specific question to ask the team."
Safety/Checks: Ask the model to mark any items sourced from uncertain or unsourced statements. Require that the assistant appends a short confidence score (low/medium/high) for each action and a list of exact phrases from the notes it used to infer the action.
Inputs: decision description, participants, rationale, alternatives considered, timestamp.
Instruction: "Format a decision log entry with: Title, Decision Statement, Rationale (short), Alternatives Considered, Deciders, Effective Date, Next Review Date (if any). Keep language neutral and cite the sentence(s) from the input that justify the rationale."
Safety/Checks: Ensure the assistant does not invent deciders — if not explicit, prompt it to mark 'decider unknown.'
Drafting — emails, decision memos, and announcements
Templates for consistent tone, clarity, and inclusion of required fields.
Inputs: recipient role or name, purpose, key points, desired call-to-action, tone (friendly/formal), length limit.
Instruction: "Draft an email with a clear subject line, a 2–3 sentence opening that states the purpose, 3 bullet points with supporting details, and a single clear call-to-action. Provide a subject line and two alternative opening lines with slightly different tones."
Safety/Checks: Add a checklist at the end of the draft: GDPR/privacy checks, claims that require verification, and any phrases that could be misinterpreted.
Inputs: decision question, options (short list), recommended option, supporting data, risks, stakeholders impacted, timeline.
Instruction: "Create a one-page decision memo with: Purpose, Background (3–4 lines), Options (with pros/cons), Recommendation (with 2–3 supporting facts), Implementation risks & mitigations, and Next Steps. Use headings and bullet lists for readability."
Safety/Checks: Require sources or data references for supporting facts; flag any recommendations that rely on missing data.
Research — question framing and source reminders
Help the assistant discover actionable, attributable information rather than speculative answers.
Inputs: research question, allowed source types (peer-reviewed, internal docs, dated news, blogs), date range, desired output length.
Instruction: "Provide a 150–300 word brief summarizing the current state of knowledge, 3–5 bullet-point implications for our team, and 3 reliable sources (with URLs or citations). Indicate confidence for each implication and note where evidence is weak or mixed."
Safety/Checks: Insist on citations. If no reliable sources are found, produce a 'what we don't know' section and suggested next steps to obtain primary data.
Inputs: question, list of internal documents or folders to prioritize, whether to include external sources.
Instruction: "Answer the question using only the listed sources. For each claim, cite the source (doc title, section, page). If the sources don't answer fully, return 'Insufficient internal evidence' and propose 2 targeted follow-up queries or data requests."
Safety/Checks: Strict source constraint prevents hallucination. The assistant should explicitly refuse to answer outside the scope.
Facilitation — agendas, scripts, and prompts to run live exercises
Used to design effective meetings and structured conversations.
Inputs: workshop goal, attendee roles, available time, desired outputs (e.g., prioritized list, prototype, decision), constraints.
Instruction: "Produce a time-boxed agenda with minute-by-minute segments, facilitator script prompts for each segment, required materials, and a 3-question evaluation to collect immediate feedback. Mark which segments require prework and who should prepare it."
Safety/Checks: Include accessibility and psychological safety notes (e.g., mechanism for silent input, how to handle dominant voices).
Inputs: brief description of the disagreement, stakeholders, examples of recent interactions, desired outcome.
Instruction: "Draft a neutral, facilitative script to surface assumptions and interests. Provide 5 questions a facilitator can use, and a suggested 10-minute exercise to elicit priorities. Add a short 'when to escalate' checklist."
Safety/Checks: Advise to avoid naming individuals in shared notes; recommend a private follow-up when sensitive information appears.
Agent Handoffs & Playbook Patterns
Common multi-step patterns that combine assistant outputs with human review or secondary agents.
- Extract → Prioritize → Assign: Use the meeting notes prompt to extract candidate actions, then run a prioritization prompt (criteria: impact, effort, risk), then produce an assignment list for human reviewers to confirm.
- Draft → Review → Localize: Generate a first draft (email or memo), then run an explicit review prompt that checks for policy or legal flags, then produce localized versions for different audiences.
- Research → Summarize → Source-check: Produce research brief, then run a source-check agent that verifies links and publication dates and flags paywalled or unreliable sources.
Guardrails & Attribution
- Require citations for factual claims and list where the assistant was uncertain.
- Label speculative language clearly (e.g., "Hypothesis", "Assumption").
- Always include a human-in-the-loop step before external publication of decisions, announcements, or legal/HR-sensitive communications.
- Use targeted constraints to limit hallucination ("Use only these sources", "Do not invent dates or names").
Quick Checklist Before Sharing an AI Output
- Confirm the source(s) for any factual claim and add citations.
- Verify assignment owners and due dates with the team (don’t infer if not explicit).
- Scan for sensitive content and remove or escalate as needed.
- Ask the assistant for a one-line confidence level and a short list of statements that were assumptions.
Next Steps & Capability Opportunities
This library is a living resource. Consider packaging common patterns as interactive templates that capture: prompt text, required inputs, expected output format, and post-output checks. Track prompt performance (time saved, edits required, error rates) and iterate on templates with your team.
Discussion
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