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meeting_followup_generate_followup_artifacts

Generate meeting follow-up artifacts in parallel: email, CRM notes, tasks, and team update from transcript and coaching data.

Instructions

Generates all followup deliverables in parallel: email draft, CRM notes, task list, and team update.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
transcript_analysisYesThe analysis from Analyze Transcript action.{{transcript_analysis}}
coaching_insightsYesInsights from Generate Coaching action.{{coaching_insights}}
user_contextNoUser context from Load Followup Context action.{{followup_context}}
user_context_dataNoRaw user.context data as fallback for user name/role.{{user.context}}
enriched_eventYesThe enriched event data with meeting info.{{enriched_event}}
fast_modelNoModel for CRM notes, tasks, and team update.gpt-5-mini
quality_modelNoModel for follow-up email (higher quality).gpt-5
team_channelNoSlack channel for team update.#sales-team
output_variable_nameYesVariable name to store all generated artifacts.followup_artifacts
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden for behavioral disclosure. It only mentions parallel generation and lists output types, but omits details on side effects, rate limits, error handling, or dependencies on other tool outputs. Critical for a complex follow-up tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, front-loaded with verb and core action. Every word is relevant. No redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has 9 parameters, 4 required, and no output schema. Description only gives high-level output list, but fails to explain workflow, input dependencies (e.g., transcript_analysis likely from another tool), or structure of returned artifacts. Incomplete for effective invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description does not add meaning beyond parameter descriptions in the schema. It briefly mentions outputs but not how parameters influence behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the primary action (generates) and lists specific deliverables (email draft, CRM notes, task list, team update) performed in parallel. It distinguishes from sibling tools like meeting_followup_analyze_transcript that focus on individual steps.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit when or when-not guidance is provided. The description implies this is a final aggregation step, but does not mention prerequisites like having transcript analysis or coaching insights, nor does it compare to alternatives like generate_coaching or analyze_transcript.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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