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 meeting-to-dealgit 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/meeting-to-deal)<a href="https://agentmods.dev/skills/mondaycom/mcp/meeting-to-deal"><img src="https://agentmods.dev/badge/skills/mondaycom/mcp/meeting-to-deal/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/meeting-to-deal"><img src="https://agentmods.dev/badge/skills/mondaycom/mcp/meeting-to-deal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 18 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high Prompt Injection · line 173 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high Prompt Injection · line 198 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high Prompt Injection · line 322 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00107 | $0.05590 |
| Opus 5 | $0.00053 | $0.02795 |
| Sonnet 5 | $0.00021 | $0.01118 |
| Haiku 4.5 | $0.00011 | $0.00559 |
Grade A, and why
meeting-to-deal 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 11d 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 — 382 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting to Opportunity
Flow: Trigger → Pull meetings → Match → Synthesize → Publish (α) → Auto-contact (β, opt-in) → Proactive next-step nudges (opt-in).
Input
- Optional: time window via argument (default = last 24h).
- Optional: pre-declared mode (Default / Silent / Proactive).
Output
- α (default): One
Meeting recapupdate per matched deal, summarizing key points + commitments + next steps. Body carries theGenerated by Claude · <ISO timestamp>footer +<!-- claude-skill-id: meeting-to-deal --><!-- meeting-id: <id> -->comments. AMeeting sync — <Mon DD>doc lists what was matched, what wasn't, and unresolved attendees. - β (Auto-contact, opt-in): New items on the Contacts board for meeting attendees not already in CRM, linked back to the matched deal. Each new contact carries
Source = Claudeon a status column. - Proactive extension:
create_notificationto deal owner for commitments due this week. Stage column edits and last-touch updates are also OK in Proactive (or in Default with batched confirm) when a clear transition phrase is present in the transcript ("we agreed to move to procurement review", "they signed today"). Surfaced as a single batched plan: " stage transitions detected. Apply all / review each / skip stage edits?". Amount-column writes still forbidden.
Knowledge
- Meeting → deal matching heuristic (§ Step 4).
- Update body convention (§ Step 6).
- Shared artifact conventions (§ Shared patterns).
Tools (MCP)
get_user_context— user identity + email domain for filtering meetings and extractinginternal_domain.get_notetaker_meetings— recent meetings + transcripts.search/list_workspaces/get_board_info— locate Deals + Contacts boards.get_board_items_page— fetch active deals to match against.get_column_type_info— resolve email/company columns by type.create_update— write the recap onto the matched deal.create_item— β auto-contact on the Contacts board.change_item_column_values— populate the new contact's email + company columns, writeSource = Claudeon contacts, and apply confirmed stage / last-touch edits on matched deals. Never for amount columns.create_notification— proactive next-step nudges.create_doc— sync summary doc.all_monday_api— escape hatch for connect-board column writes (linking contact ↔ deal). Note: connect-board writes viaall_monday_apimay fail silently — see Error handling reference.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 382 lines · 107 tokens per session scan A ef4eb9491279
meeting-to-deal is a skill published in the GitHub repository mondaycom/mcp (424 stars, last pushed yesterday), licensed MIT. It adds 107 tokens to every session and 5,590 once invoked, about $0.0005 per session on Opus 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.
Other skills, from other repositories
init-workspace-flow
Workflow for initializing or upgrading a workspace: context, discovery, documentation, etc.
arrange-workspace-flow
Workflow for arranging a workspace: layout, reference source code, business/technical context, ecosystem setup.
github-triage
Triage GitHub issues through a label-based state machine with interactive grilling sessions. Use when user wants to triage issues, review incoming bugs or feature requests, prepare issues for an AFK agent, or manage issue workflow.
paseo
Paseo reference for managing projects, workspaces, workspace scripts, agents, schedules, and heartbeats.
testgen-flow
Workflow for generating test cases from requirements (Issue Tracker / Wiki sources), exporting to a Test Management System, etc.
backlog
To validate story readiness for a sprint or to break work into a human WBS.