Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mondaycom/mcp --skill activity-insightsgit clone --depth 1 https://github.com/mondaycom/mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mondaycom/mcp/activity-insights)<a href="https://agentmods.dev/skills/mondaycom/mcp/activity-insights"><img src="https://agentmods.dev/badge/skills/mondaycom/mcp/activity-insights/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mondaycom/mcp/activity-insights"><img src="https://agentmods.dev/badge/skills/mondaycom/mcp/activity-insights.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00098 | $0.01593 |
| Opus 5.5 | $0.00039 | $0.00637 |
| Sonnet 5.5 | $0.00020 | $0.00319 |
| Haiku 4.5 | $0.00010 | $0.00159 |
Grade A, and why
activity-insights scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Activity Insights
Flow: Trigger → Connector check → Resolve board → Build query → Fetch insights → Synthesize.
Input
- Optional: argument describing the analysis (e.g., "rep activity this week", "call breakdown for the team").
- Optional: rep name, date range, or grouping preference.
Output
A synthesized summary with specific numbers and rep-level breakdowns. Never raw JSON.
Knowledge
get-activity-insightsreturns aggregated counts — not individual activity records. For activity history with content, useget-timeline-items.- Default time range is 7 days — no need to pass a date if the user asks about "recent" or "this week".
- groupBy accepts 1–2 fields:
["type"]for activity breakdown;["userId", "type"]for per-rep breakdown;["userId"]for rep totals only. board_idis required — always resolve it before calling the tool.- Present results as natural language insights — never dump the raw results array.
Tools (MCP)
get-activity-insights— aggregated activity stats (counts, duration) grouped by rep, type, or item.get_user_context— user identity and account info.search/get_board_info/get_board_items_page— resolve boards and items.list_users_and_teams— resolve rep names to user IDs for filtering.get-timeline-items— fallback for item-level activity detail (content, not aggregates).
When to use each groupBy
| User says | groupBy | Notes |
|---|---|---|
| "How many calls did each rep make?" | ["userId", "type"] |
Per-rep breakdown |
| "What's the activity breakdown this week?" | ["type"] |
Team totals by type |
| "Who's the most active rep?" | ["userId"] |
Rep totals only |
| "How many emails did John send?" | ["type"] |
+ userIds filter |
| "Activity on the Acme deal?" | ["type"] |
+ itemIds filter — or use get-timeline-items for content |
| "Compare rep performance last month" | ["userId", "type"] |
Set fromDate/toDate |
Step 0: Connector check
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 132 lines · 98 tokens per session scan A e9c1ad8713c3
activity-insights is a skill published in the GitHub repository mondaycom/mcp (433 stars, last pushed today), licensed MIT. It adds 98 tokens to every session and 1,593 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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