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.
npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill transcript-replaygit clone --depth 1 https://github.com/hoangsonww/Claude-Code-Agent-MonitorWrote 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.
[](https://agentmods.dev/skills/hoangsonww/claude-code-agent-monitor/transcript-replay)<a href="https://agentmods.dev/skills/hoangsonww/claude-code-agent-monitor/transcript-replay"><img src="https://agentmods.dev/badge/skills/hoangsonww/claude-code-agent-monitor/transcript-replay/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.
<a href="https://agentmods.dev/skills/hoangsonww/claude-code-agent-monitor/transcript-replay"><img src="https://agentmods.dev/badge/skills/hoangsonww/claude-code-agent-monitor/transcript-replay.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00069 | $0.00609 |
| Opus 5 | $0.00034 | $0.00304 |
| Sonnet 5 | $0.00014 | $0.00122 |
| Haiku 4.5 | $0.00007 | $0.00061 |
Grade A, and why
transcript-replay 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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) orerrorsto 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.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 60 lines · 69 tokens per session scan A 654b0bec75c8
transcript-replay is a skill published in the GitHub repository hoangsonww/Claude-Code-Agent-Monitor (989 stars, last pushed 2d ago), licensed MIT. It adds 69 tokens to every session and 609 once invoked, about $0.0003 per session on Opus 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.
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