Claude Skill

transcript-replay

Walk a Claude Code session transcript turn-by-turn from Agent Monitor data, summarizing each user, assistant, and tool message in order so a long conversation can be reviewed quickly. Anchors the recap to the session header (model, cost, turn_count). Use when reviewing what was a

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hoangsonww/claude-code-agent-monitor 1014 238 forks MIT Updated 22h ago

Part of hoangsonww/claude-code-agent-monitor — 86 skills

Install

skills CLI

npx skills add https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-sessions/skills/transcript-replay

Claude Code

claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install hoangsonww-claude-code-agent-monitor@llmmart

Git git clone https://github.com/hoangsonww/Claude-Code-Agent-Monitor.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole hoangsonww/claude-code-agent-monitor collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

Transcript Replay

Replay a session transcript one turn at a time with a concise summary of each message.

Input

The user provides: $ARGUMENTS

A session ID to replay, or
"latest" / "last" for the most recent session.
Optionally a turn range (e.g. 1-10) or errors to focus on tool failures.

Data Sources

Endpoint	Returns
`GET /api/sessions/:id/transcript`	ordered transcript messages: role (user / assistant / tool), content, tool_name and tool result where applicable, timestamps
`GET /api/sessions/:id`	session header: status, model, cwd, started_at, ended_at, cost, metadata (thinking_blocks, turn_count, total_turn_duration_ms)

Report Sections

1. Header

GET /api/sessions/:id. Print id, model, cwd basename, status, turn_count, thinking_blocks, total_turn_duration_ms, and cost in one block.

2. Turn-by-turn walk

GET /api/sessions/:id/transcript. Iterate messages in order. For each turn emit one compact entry:

user — the request in one sentence (quote the literal ask only if short).
assistant — the decision / action taken, plus which tools it invoked.
tool — the tool name and a one-line result (success value or the error text); do not paste large tool payloads.

Group an assistant message with the tool calls it triggered so each "turn" reads as intent → action → result.

3. Thread highlights

After the walk, pull out: the original goal, the key turning points, any tool failures or retries, and how the session ended (resolved / errored / abandoned).

Output

A numbered turn list (Turn N — <role>: <one-line summary>), grouped intent → action → result, preceded by the header block and followed by the highlights. Truncate any quoted content past ~200 chars with …. Currency as USD to 4 decimal places. Summarize faithfully — never invent message content that is not in the transcript. If the transcript endpoint returns empty, say the session has no stored transcript (it may predate transcript capture or need a reimport) rather than fabricating turns. If the dashboard is unreachable, tell the user to start it with npm start from the repo root.

Files (claude-code-agent-monitor)

agents

openai.yaml 271 B

interface:
  display_name: "Transcript Replay"
  short_description: "Walk a Claude Code session transcript turn-by-turn from..."
  default_prompt: "Use $transcript-replay to inspect CCAM data and complete this workflow safely."
policy:
  allow_implicit_invocation: false

SKILL.md 2.5 KB

---
name: transcript-replay
description: >
  Walk a Claude Code session transcript turn-by-turn from Agent Monitor data,
  summarizing each user, assistant, and tool message in order so a long conversation
  can be reviewed quickly. Anchors the recap to the session header (model, cost,
  turn_count). Use when reviewing what was actually said and done in a conversation.
---

# Transcript Replay

Replay a session transcript one turn at a time with a concise summary of each message.

## Input

The user provides: **$ARGUMENTS**

- A **session ID** to replay, or
- "latest" / "last" for the most recent session.
- Optionally a turn range (e.g. `1-10`) or `errors` to focus on tool failures.

## Data Sources

| Endpoint | Returns |
|----------|---------|
| `GET /api/sessions/:id/transcript` | ordered transcript messages: role (user / assistant / tool), content, tool_name and tool result where applicable, timestamps |
| `GET /api/sessions/:id` | session header: status, model, cwd, started_at, ended_at, cost, metadata (thinking_blocks, turn_count, total_turn_duration_ms) |

## Report Sections

### 1. Header
`GET /api/sessions/:id`. Print id, model, cwd basename, status, turn_count,
thinking_blocks, total_turn_duration_ms, and cost in one block.

### 2. Turn-by-turn walk
`GET /api/sessions/:id/transcript`. Iterate messages in order. For each turn emit
one compact entry:
- **user** — the request in one sentence (quote the literal ask only if short).
- **assistant** — the decision / action taken, plus which tools it invoked.
- **tool** — the tool name and a one-line result (success value or the error text);
  do not paste large tool payloads.

Group an assistant message with the tool calls it triggered so each "turn" reads as
intent → action → result.

### 3. Thread highlights
After the walk, pull out: the original goal, the key turning points, any tool
failures or retries, and how the session ended (resolved / errored / abandoned).

## Output

A numbered turn list (`Turn N — <role>: <one-line summary>`), grouped intent →
action → result, preceded by the header block and followed by the highlights.
Truncate any quoted content past ~200 chars with `…`. Currency as USD to 4 decimal
places. Summarize faithfully — never invent message content that is not in the
transcript. If the transcript endpoint returns empty, say the session has no stored
transcript (it may predate transcript capture or need a reimport) rather than
fabricating turns. If the dashboard is unreachable, tell the user to start it with
`npm start` from the repo root.