Plugins

1 plugin

Conversational derivation engine — generate agent-native memory architecture from natural conversation. 15 kernel primitives, 26 commands, 17 feature blocks, 3 presets.

10 skills · plugin

Results for “conversation”

9 skills

Chatbot Analytics

Implement AI chatbot analytics and conversation monitoring. Use when adding conversation metrics, tracking AI usage, measuring user engagement with chat, or building conversation dashboards. Activates for AI analytics, token tracking, conversation categorization, and chat performance.

X Tweet By Conversation

Collects every tweet in an X (Twitter) conversation thread given a conversation id, returning normalized per-tweet data with text, author, engagement counts, media, hashtags, mentions, and reply mapping.

Search and analyze conversation history stored in session JSONL files using jq and shell commands.

Query Gong conversation intelligence APIs to list calls, fetch transcripts, manage users, and retrieve activity stats.

More results

Gong Automation

Retrieve call transcripts, analytics, speaker stats, and workspace data from Gong conversation intelligence using natural language commands.

johnalbertini14-glitch

Search and retrieve Gong call recordings, transcripts, user lists, and activity statistics via the Gong API.

Search and retrieve Gong call recordings, transcripts, users, and activity stats via the Gong API.

Synthesizes recent conversations about any topic across Reddit, Hacker News, the open web, and optionally X/Twitter into a single briefing with citations, engagement metrics, and cross-platform pattern analysis.

20.4k · bundle

Rulebase Workspace SQL

Use when querying a Rulebase workspace with SQL through the MCP server's query tool — writing queries that finish inside the statement timeout, and avoiding the join fan-outs that silently inflate QA evaluation counts. Trigger for "query my Rulebase data", "the query timed out", "statement timeout", "canceling statement due to statement timeout", counts that don't reconcile between two Rulebase queries, criterion counts exceeding team counts, or any multi-step analysis over Rulebase conversations and evaluations.