OpenSRE is an open-source framework for building AI agents that investigate and resolve production incidents using operational data and tools. It is for site reliability engineers who want customizable incident-response workflows, training, and evaluation on their own infrastructure.
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 Tracer-Cloud/opensre --skill summarizing-posthog-analyticsgit clone --depth 1 https://github.com/Tracer-Cloud/opensreWrote 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/tracer-cloud/opensre/summarizing-posthog-analytics)<a href="https://agentmods.dev/skills/tracer-cloud/opensre/summarizing-posthog-analytics"><img src="https://agentmods.dev/badge/skills/tracer-cloud/opensre/summarizing-posthog-analytics/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/tracer-cloud/opensre/summarizing-posthog-analytics"><img src="https://agentmods.dev/badge/skills/tracer-cloud/opensre/summarizing-posthog-analytics.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 | $0.00053 | $0.01195 |
| Opus 5.5 | $0.00021 | $0.00478 |
| Sonnet 5.5 | $0.00011 | $0.00239 |
| Haiku 4.5 | $0.00005 | $0.00120 |
Grade A, and why
summarizing-posthog-analytics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PostHog Summary
PostHog product-analytics reporting for chat delivery. Produce a per-metric pulse over a window — what moved, why it matters — not a raw dashboard export. Single source (PostHog MCP); finish here, then optionally suggest a multi-source follow-up.
Requires the PostHog MCP integration (posthog_mcp). The REST-only
posthog integration cannot serve this skill.
1. Discover
list_posthog_tools once with name_filter: "insights dashboard sql events" to
find the query surface. Then call read-data-schema (or the equivalent schema
tool) BEFORE any aggregation query and only reference events and properties it
confirms exist. Do not reference a property (e.g. properties.$mcp_error)
without seeing it in the schema first — HogQL rejects queries against unknown
properties. To pull metric data, use call_posthog_tool with
tool_name: "execute-sql" and SQL as a top-level string:
{
"tool_name": "execute-sql",
"arguments": { "query": "SELECT count() FROM events WHERE event = '$pageview'" }
}
Never nest the SQL ({"query": {"query": "SELECT …"}}) — PostHog rejects that
with parameter "query" must be of type string. Use insight/dashboard tools
when the user names a specific dashboard.
2. Fetch metrics
Map user words to windows:
- 24h — "today", "overnight", morning report
- 7d — "this week", default weekly report
- 30d — "this month", monthly rollup
Run one small HogQL query per metric — do NOT combine multiple metrics into a
single aggregated statement, and never cross-join events against synthetic
"window" rows. That combined shape is the most common cause of PostHog's
unknown error running this query. Return only aggregate numbers (two
columns: current / previous) — never event-level rows. Compute the two windows
with an explicit conditional aggregate over a single time filter, e.g.:
SELECT
countIf(timestamp >= now() - INTERVAL 7 DAY) AS current,
countIf(timestamp >= now() - INTERVAL 14 DAY
AND timestamp < now() - INTERVAL 7 DAY) AS previous
FROM events
WHERE event = '$pageview'
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.
- 1mo ago First seen · 113 lines · 53 tokens per session scan A 6d17fac65df9
summarizing-posthog-analytics is a skill published in the GitHub repository Tracer-Cloud/opensre (11,969 stars, last pushed today), licensed Apache-2.0. It adds 53 tokens to every session and 1,195 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 2026-09-10.
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