| name | activity-brief |
| description | Give a time-bucketed league activity briefing on recent fantasy moves, including who moved who, when, and why. Use when the user explicitly wants a transaction roundup or invokes /activity-brief. |
| argument-hint | [days-back, default 2] |
| license | Proprietary |
Activity Brief
Produce a clean recent-activity briefing for the user's current or specified fantasy league.
Scope and data rules
- Fantasy league data must come from Flaim MCP tools.
- Use web search to enrich player news, injuries, role changes, and schedule context.
Arguments
$ARGUMENTS is the requested number of days back.- If no argument is provided, default to
2.
- Treat non-numeric arguments as no argument unless the user clearly explains a different time window in natural language.
Workflow
1. Resolve the target league
- Call
get_user_session if it has not already been called in this chat.
- If the user explicitly names a league, platform, or sport, honor that.
- Otherwise treat this as a vague singular request: use
defaultLeague when present, otherwise the relevant sport entry in defaultLeagues.
- If there is no applicable default and multiple leagues still match, ask which league.
- Call
get_league_info for the selected league before interpreting transactions so team names and owner/team mapping are resolved.
2. Pull recent transactions
- For daily or 24-hour briefs, call
get_transactions with the default count or explicit count: 25.
- Use a larger count such as
count: 40 only when the requested window is busier or longer than a normal daily brief.
- Do not use
count: 100 unless the user asks for an exhaustive or full-week activity audit.
- Retrieve the recent transaction window the platform provides, then trim the presentation to the requested day range.
- Remember platform caveats:
- Yahoo ignores explicit
week and uses a recent timestamp window.
- ESPN and Sleeper are more week-oriented than date-oriented.
3. Organize the results
Bucket the transactions by time period relative to now:
- Overnight: since the most recent midnight in the user's inferred timezone, or UTC if their timezone is unclear
- Yesterday: the prior calendar day
- Prior day(s): older moves still within the requested window
Within each time bucket, group by team so the user can see what each team did together.
4. Enrich with public context
For the important players involved, use web search to check:
- injuries or status changes
- recent performance trends
- role or depth-chart changes
- upcoming schedule context
- breaking news that explains the move
5. Analyze each move
- Simple adds/drops: usually one line
- Waiver claims: one line explaining the appeal of the add and what was sacrificed
- Trades: a few lines on what each side gains, schedule implications, and whether it looks balanced
Focus on why the move likely happened, not just what the transaction log says.
6. Present the briefing
Format the output as:
- one-sentence topline summary
- time-bucketed sections
- team-grouped moves inside each section
- short take on any move that materially affects the user's team or competition
Output style
- Conversational, not robotic
- Player names in bold on first mention
- Keep simple moves to one line when possible
- Expand only when a trade or high-impact move justifies it
