claude-code-logfire-plugin CLAUDE.md

Repository instructions for a Claude Code plugin that records coding sessions and sends compatible traces to Pydantic Logfire, with a local JSONL file as a fallback. JSONL is a text format with one JSON record per line, while OpenTelemetry (OTel) is a standard for collecting traces.

In plain words
What is it for?
Use them when modifying or testing the plugin, especially its event logging, local session records, Logfire uploads, configuration, or repository files.
Why use it?
They explain the plugin’s single-script architecture, event hooks, session state, trace linking, dependencies, and testing so changes fit the existing design.

Instructions file

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.

agentmods
npx agentmods add instructions/pydantic/claude-code-logfire-plugin/claude-md
Clone the repo
git clone --depth 1 https://github.com/pydantic/claude-code-logfire-plugin
Per session 995 This file is loaded in full into every session.
When invoked 995 The same file — it is already loaded in full.
Security scan A 1 finding. Scan, not verified.
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 $0.00995 $0.00995
Opus 5 $0.00498 $0.00498
Sonnet 5 $0.00199 $0.00199
Haiku 4.5 $0.00100 $0.00100

Measured 2d ago against content hash 17a458a60200, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

claude-code-logfire-plugin CLAUDE.md scanned grade A with 1 finding 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 2d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

**Data flow:** Claude Code hook fires -> stdin JSON piped to `log-event.py` -> appends JSONL locally -> if `LOGFIRE_TOKEN` set and event is SessionStart/Stop/SubagentStop/SessionEnd, builds OTLP/HTTP JSON payload and sen
CLAUDE.md · 67 lines

How it starts

The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

What This Is

A Claude Code plugin that captures sessions and exports pydantic-ai compatible OTel traces to Pydantic Logfire, with local JSONL fallback. The plugin is a single Python 3 script (stdlib only, no external dependencies).

Architecture

The entire plugin is a single Python script (scripts/log-event.py) invoked by every hook event defined in hooks/hooks.json. The plugin manifest lives at .claude-plugin/plugin.json.

Data flow: Claude Code hook fires -> stdin JSON piped to log-event.py -> appends JSONL locally -> if LOGFIRE_TOKEN set and event is SessionStart/Stop/SubagentStop/SessionEnd, builds OTLP/HTTP JSON payload and sends via urllib.

Session state: A temp file ($TMPDIR/claude-logfire-{session_id}.json) persists the root span ID, start time, transcript line offset, accumulated messages, usage totals, and cost details between hook invocations. Created on SessionStart, deleted on SessionEnd.

Trace correlation: trace_id is deterministically derived from session_id via SHA-256.

Span hierarchy (pydantic-ai style):

agent run (root span)              <- the session (emitted on SessionEnd)
├── chat claude-opus-4-6           <- LLM API call 1 (emitted on Stop)
├── chat claude-opus-4-6           <- LLM API call 2 (emitted on Stop)
└── chat claude-opus-4-6           <- LLM API call 3 (emitted on Stop)

OTLP processing model:

Hook Event JSONL OTLP
SessionStart yes pending root span (logfire.span_type=pending_span)
Stop / SubagentStop yes "chat {model}" child spans per LLM API call
SessionEnd yes finalized root "agent run" span with all_messages, usage, cost
All other events yes none (early exit)

Transcript parsing: On Stop events, the script reads new transcript lines (since last offset), deduplicates streaming fragments by message.id, identifies API call boundaries, and converts messages to pydantic-ai format (tool_use -> tool_call, tool_result -> tool_call_response, end_turn -> stop).

Read the full file on GitHub · 67 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. 2d ago First seen · 67 lines · 995 tokens per session scan A 17a458a60200

Subscribe to this mod's changes

claude-code-logfire-plugin CLAUDE.md is an instructions file published in the GitHub repository pydantic/claude-code-logfire-plugin (15 stars, last pushed 2mo ago), licensed MIT. It adds 995 tokens to every session, about $0.0050 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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