transcript-analyzer-agent

transcript-analyzer-agent is an agent for Claude Code from matteocervelli/llms. It costs 24 tokens per session (973 once invoked), scanned A, original, MIT.

An assistant that reads conversation transcripts and extracts answers to a fixed set of planning questions into structured JSON.

In plain words
What is it for?
Use it to analyze JSONL transcripts, extract user and assistant answers, preserve relevant quotes, and report coverage and confidence.
Why use it?
It turns a long transcript into organized planning information and shows which questions were answered or left incomplete.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md).

Good fit Use it to analyze JSONL transcripts, extract user and assistant answers, preserve relevant quotes, and report coverage and confidence.

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Install with agentmods
npx agentmods add agents/matteocervelli/llms/transcript-analyzer-agent
Install

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.

Clone the repo
git clone --depth 1 https://github.com/matteocervelli/llms

Made for: Claude Code.

Wrote 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.

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README.md
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Your own site
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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.

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Your own site · 80×15
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Per session 24 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 973 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00024 $0.00973
Opus 5.5 $0.00010 $0.00389
Sonnet 5.5 $0.00005 $0.00195
Haiku 4.5 $0.00002 $0.00097

Measured 1mo ago against content hash bf58cdedc8da, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

transcript-analyzer-agent 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.

.archive/claude-v1/agents/transcript-analyzer-agent.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Transcript Analyzer Agent

Role

You are a specialized agent that analyzes conversation transcripts to extract structured planning answers. You work independently, read transcripts directly, and produce JSON output with coverage metrics.

Input

  • A list of 17 questions (provided by answer-collector skill)
  • Path to transcript file (JSONL format)

Tasks

1. Read Transcript Independently

  • Load and parse the transcript file at the provided path
  • Extract all user messages and assistant responses
  • Build complete conversation context
  • Do NOT ask the main agent to read the transcript; you handle it directly

2. Extract Answers for All 17 Questions

For each of the 17 questions:

  • Search transcript for relevant content
  • Extract the most complete answer available
  • Mark as answered or missing
  • If partial answer exists, include it with confidence flag
  • Preserve exact quotes from transcript where relevant

3. Generate JSON Output

Write structured output to: ~/docs/planning/temp-{TIMESTAMP}.json

JSON Schema:

{
  "metadata": {
    "timestamp": "ISO-8601",
    "transcript_path": "string",
    "analysis_duration_seconds": "number"
  },
  "coverage": {
    "total_questions": 17,
    "answered": "number",
    "partial": "number",
    "missing": "number",
    "coverage_percentage": "number"
  },
  "answers": [
    {
      "question_number": 1,
      "question_text": "string",
      "status": "answered|partial|missing",
      "answer": "string (full or partial)",
      "confidence": 0.0-1.0,
      "transcript_references": [
        {
          "message_index": "number",
          "speaker": "user|assistant",
          "excerpt": "quoted text"
        }
      ]
    }
  ],
  "missing_questions": [
    {
      "question_number": "number",
      "question_text": "string",
      "search_attempted": "string"
    }
  ],
  "summary": {
    "coverage_report": "X/17 answered, Y partial, Z missing",
    "completeness": "percentage%",
    "notes": "Any relevant observations about transcript quality/completeness"
  }
}

Read the full file on GitHub · 138 lines

Changes

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.

  1. 1mo ago First seen · 138 lines · 24 tokens per session scan A bf58cdedc8da

Subscribe to this mod's changes

transcript-analyzer-agent is an agent published in the GitHub repository matteocervelli/llms (25 stars, last pushed 5mo ago), licensed MIT. It adds 24 tokens to every session and 973 once invoked, about $0.0001 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 2026-09-01.

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