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 PostHog/posthog-foss --skill finding-llm-gateway-migration-candidatesgit clone --depth 1 https://github.com/PostHog/posthog-fossWrote 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/posthog/posthog-foss/finding-llm-gateway-migration-candidates)<a href="https://agentmods.dev/skills/posthog/posthog-foss/finding-llm-gateway-migration-candidates"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/finding-llm-gateway-migration-candidates/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/posthog/posthog-foss/finding-llm-gateway-migration-candidates"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/finding-llm-gateway-migration-candidates.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 | $0.00096 | $0.01379 |
| Opus 5 | $0.00048 | $0.00690 |
| Sonnet 5 | $0.00019 | $0.00276 |
| Haiku 4.5 | $0.00010 | $0.00138 |
Grade A, and why
finding-llm-gateway-migration-candidates 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 11d 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Finding LLM gateway migration candidates
Use services/llm-gateway/PARITY.md as the current contract decision record. If implementation evidence contradicts it, run /auditing-llm-gateway-parity before ranking candidates.
This skill produces a point-in-time shortlist. Do not turn the parity document into a fleet-wide migration tracker.
Discover callers
Search the current default branches for Python gateway use, including:
LLM_GATEWAY_URL,LLM_GATEWAY_API_KEY, and product-slug URLsget_llm_client,get_async_llm_client, andget_async_anthropic_gateway_client- direct OpenAI, Anthropic, or agent SDK clients configured with a gateway base URL
- Python product names from
services/llm-gateway/src/llm_gateway/products/config.py - deployment, sandbox, workflow, and secret wiring in other PostHog repositories
Trace each result to the production call site. Exclude tests, development-only tools, dead code, and callers already configured exclusively for Go. Treat shared worker configuration as evidence about availability, not proof that every call in that process uses Go.
Search open and recently merged PRs across involved repositories before proposing work. A migration may already be underway even when the default branch still uses Python.
Prove the production path
Before classifying a caller, follow it through every runtime boundary:
- Find the API, task, workflow, schedule, or command that invokes it.
- For Temporal, map the workflow and activity to the exact task queue, then map that queue to its deployed worker.
- Inspect every environment overlay that runs the caller. Do not borrow configuration from another worker in the same product.
- Resolve the configured URL by host and path. Variable names are not proof: an
AI_GATEWAY_URLcan still contain a Python product-slug URL. - Confirm the current call can succeed. A broad exception handler with a deterministic fallback can hide missing credentials or a route that never runs.
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.
- 11d ago First seen · 95 lines · 96 tokens per session scan A e6eb2480fc4b
finding-llm-gateway-migration-candidates is a skill published in the GitHub repository PostHog/posthog-foss (715 stars, last pushed yesterday), licensed MIT. It adds 96 tokens to every session and 1,379 once invoked, about $0.0005 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 2026-08-30.
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