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Conversation Analyzer

Checked
mhattingpete·vlatest·other·Apache-2.0

This tool analyzes conversations to identify key themes, sentiment, and entities, providing valuable insights for understanding communication patterns.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add mhattingpete/claude-skills-marketplace --skill conversation-analyzer -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

mhattingpete

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned mhattingpete/claude-skills-marketplace at b5b34bcf4c.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
b5b34bcf4c
Manifest
productivity-skills-plugin/skills/conversation-analyzer/SKILL.md
Scanned
2 files, 502 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

The conversation-analyzer skill provides a structured framework for dissecting dialogue interactions, breaking them down into distinct components like intent, sentiment, and context. It enables AI agents to move beyond simple text matching by offering deep insights into the underlying dynamics of a conversation.

When to use it

  • Diagnosing why an agent failed to resolve a user's issue during a specific turn.
  • Evaluating the emotional tone of customer support chats to identify frustration spikes.
  • Auditing training data conversations for clarity and logical flow before deployment.
  • Debugging complex multi-turn interactions where context was lost or misunderstood.

Key capabilities

  • Decomposes dialogue into granular structural elements.
  • Identifies specific conversational intents and shifts in topic.
  • Analyzes sentiment trajectory throughout the exchange.
  • Highlights gaps in context or missing information within the flow.

Example prompts

  • "Analyze this customer support transcript to identify where the agent lost track of the user's primary goal."
  • "Break down the following dialogue into intent, sentiment, and context segments for review."
  • "Use conversation-analyzer to find specific turns in this log where the tone became negative."

Tips & gotchas

Ensure you provide a complete transcript or clearly defined turn boundaries, as fragmented input may yield incomplete structural analysis. This skill is best used when you need actionable diagnostic data rather than just a summary of what was said.