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 pydantic/skills --skill logfire-gatewaygit clone --depth 1 https://github.com/pydantic/skillsWrote 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/pydantic/skills/logfire-gateway)<a href="https://agentmods.dev/skills/pydantic/skills/logfire-gateway"><img src="https://agentmods.dev/badge/skills/pydantic/skills/logfire-gateway/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/pydantic/skills/logfire-gateway"><img src="https://agentmods.dev/badge/skills/pydantic/skills/logfire-gateway.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00052 | $0.01694 |
| Opus 5.5 | $0.00021 | $0.00678 |
| Sonnet 5.5 | $0.00010 | $0.00339 |
| Haiku 4.5 | $0.00005 | $0.00169 |
Grade A, and why
logfire-gateway 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 21d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Configure an Application with Pydantic AI Gateway
For observing or routing Claude Code/Codex itself, use coding-agent setup instead. Keep this application workflow separate from coding-session recording and provider setup.
Preserve the user's confirmed project, region, provider, and existing credential mechanism. An existing application Gateway key needs no CLI login or SDK write token. To create a key through the CLI, follow the CLI Gateway credential procedure. Use the UI's Gateway Connect flow when CLI access is unavailable.
Use this skill for model traffic, provider routing, and Gateway credentials. It
is separate from logfire-instrumentation: a Logfire write token sends
telemetry, while a Gateway key authorizes model requests. Do not substitute one
for the other. Do not configure coding-agent providers, telemetry, or MCP integrations.
A prepared setup handoff may already identify the exact project and credentials. Reuse it rather than repeating authentication or selecting another project.
1. Identify the application
Before changing files, inspect the repository and identify the existing model client, model, provider, environment loader, and runnable entrypoint. If the request names an application or the repository contains a clear inference client, wire that application through Gateway. Preserve its provider protocol and model unless the user requests a change.
If there is no inference application or the target is ambiguous, ask which application the user wants to connect. Confirm a new application's purpose before scaffolding it.
A Gateway setup request authorizes routing the selected application's model calls through Gateway. Ordinary Logfire instrumentation does not imply that choice.
Continue this setup in the current agent. A prepared wizard handoff already finished account and project selection. Do not invoke the wizard again or launch another setup agent. Preserve the existing model client, provider abstraction, dependency versions, and environment conventions.
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.
- 21d ago First seen · 157 lines · 52 tokens per session scan A f29f40062162
logfire-gateway is a skill published in the GitHub repository pydantic/skills (151 stars, last pushed 9d ago), licensed MIT. It adds 52 tokens to every session and 1,694 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 2026-10-17.
logfire-gateway compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| logfire-gatewaypydantic/skills | Skill | 151 | 9d ago | MIT | A | 52 | Claude Code |
| mem0-oss-to-platformmem0ai/mem0 | Skill | 68k | 2d ago | Apache-2.0 | A | 217 | Claude Code, Codex |
| azure-mgmt-botservice-dotnetmicrosoft/skills | Skill | 3.2k | yesterday | MIT | A | 78 | Claude Code |
| fastapi-router-pymicrosoft/skills | Skill | 3.2k | yesterday | MIT | A | 46 | Claude Code |
| dev-runtimelangwatch/langwatch | Skill | 5.0k | yesterday | Apache-2.0 | A | 172 | Claude Code |
| api-designericrisco/rsc-harness | Skill | 503 | 2d ago | MIT | A | 105 | Claude Code, Codex |
| migrate-segw-to-raparc-mcp/arc-1 | Skill | 252 | yesterday | MIT | A | 106 | Claude Code |