transcript-analyst

transcript-analyst is an agent for Claude Code from Jamie-BitFlight/claude_skills. It costs 46 tokens per session (968 once invoked), scanned A, original, MIT.

An analysis agent that examines Claude Code session transcripts using database queries and workflow-pattern analysis. It produces structured findings about recurring inefficiencies and anti-patterns.

In plain words
What is it for?
Use it to survey sessions, measure errors and tool use, find repeated sequences, compare workflows, and write findings for later improvements.
Why use it?
It replaces guesswork with evidence such as frequencies, affected sessions, and workflow patterns across the transcript collection.

Agent for Claude Code

Written for Claude Code: PreToolUse hook event. Also seen: model in frontmatter; reads .claude/ paths; mentions Claude Code.

Part of the agentskill-kaizen plugin — 4 skills, 4 commands, 2 agents shipped together

Good fit Use it to survey sessions, measure errors and tool use, find repeated sequences, compare workflows, and write findings for later improvements.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/jamie-bitflight/claude_skills/transcript-analyst
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/Jamie-BitFlight/claude_skills

Made for: Claude Code.

Or install agentskill-kaizen, the plugin that ships this one along with the rest of its 4 skills, 4 commands, 2 agents.

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.

agentmods badge for transcript-analyst

README.md
[![agentmods](https://agentmods.dev/badge/agents/jamie-bitflight/claude_skills/transcript-analyst/github.svg)](https://agentmods.dev/agents/jamie-bitflight/claude_skills/transcript-analyst)
Your own site
<a href="https://agentmods.dev/agents/jamie-bitflight/claude_skills/transcript-analyst"><img src="https://agentmods.dev/badge/agents/jamie-bitflight/claude_skills/transcript-analyst/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.

agentmods 80×15 button for transcript-analyst

Your own site · 80×15
<a href="https://agentmods.dev/agents/jamie-bitflight/claude_skills/transcript-analyst"><img src="https://agentmods.dev/badge/agents/jamie-bitflight/claude_skills/transcript-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 968 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 $0.00046 $0.00968
Opus 5.5 $0.00018 $0.00387
Sonnet 5.5 $0.00009 $0.00194
Haiku 4.5 $0.00005 $0.00097

Measured 2mo ago against content hash ae9cd4d052bb, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

transcript-analyst 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 2mo 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.

plugins/agentskill-kaizen/agents/transcript-analyst.md · 102 lines

How it starts

The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a transcript analysis specialist. Your job is to query Claude Code session transcripts and produce structured findings about anti-patterns, inefficiencies, and improvement opportunities.

Tools Available

  • DuckDB MCP (execute_query) — SQL queries against JSONL files via read_ndjson_auto()
  • Kaizen MCP — process mining tools (discover_process_model, find_frequent_patterns, cluster_sessions, extract_tool_sequences, check_conformance)
  • Read, Glob, Grep — direct file access for targeted investigation
  • Write — output findings to .planning/kaizen/

Analysis Protocol

  1. Survey the corpus first. Run a DuckDB query to count sessions, date range, and record type distribution. Report corpus size before deep analysis.

  2. Run each requested dimension. For each analysis dimension, use the appropriate tool:

    • SQL-expressible analyses (tool misuse, errors, delegation stats) → DuckDB execute_query
    • Pattern mining (workflow sequences, red herrings, session clustering) → kaizen MCP tools
    • Combined analyses → SQL for extraction, MCP for mining
  3. Quantify every finding. Every anti-pattern must include:

    • Frequency (N occurrences across M sessions)
    • Specific session IDs as evidence
    • Exact JSON field paths where the signal was found
    • Severity classification (critical / warning / info)
  4. Do not speculate. Report observed patterns with evidence. If a pattern has fewer than 3 occurrences, classify as "info" not "warning". Do not project causality — state what occurred and its frequency.

  5. Write findings to file. Output to .planning/kaizen/analysis-{YYYY-MM-DD}.md with structured sections per dimension. Include a summary table at the top.

Output Structure

# Kaizen Analysis — {date}

## Summary

| Dimension | Findings | Critical | Warning | Info |
|-----------|----------|----------|---------|------|
| Tool Misuse | 593 | 3 | 12 | 5 |
| ... | ... | ... | ... | ... |

## Dimension 1: Tool Misuse

### Finding: Bash used for file operations
- **Severity:** warning
- **Frequency:** 593 across 45 sessions
- **Evidence:** Session abc123 line 456, Session def789 line 123
- **Recommendation:** PreToolUse hook to deny Bash file-op patterns

## Dimension 2: ...

Read the full file on GitHub · 102 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. 2mo ago First seen · 102 lines · 46 tokens per session scan A ae9cd4d052bb

Subscribe to this mod's changes

transcript-analyst is an agent published in the GitHub repository Jamie-BitFlight/claude_skills (67 stars, last pushed 19d ago), licensed MIT. It adds 46 tokens to every session and 968 once invoked, about $0.0002 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 2026-09-03.

Related

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