skills/exploring-mcp-sessions/SKILL.md
Investigate individual PostHog MCP sessions — the sequence of tool calls a single agent made in one run, what it was trying to do, and where it went wrong. Use when the user asks "what did this MCP session do?", "show me the tool calls for session X", "what was the agent's goal?", "which sessions had errors?", "who is connecting to my MCP?", or pastes an MCP analytics sessions URL.
npx skillsauth add posthog/ai-plugin exploring-mcp-sessionsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
An MCP session is one agent run: the set of $mcp_tool_call events sharing a
$session_id, ordered by timestamp.
Listing sessions, reading a session's tool calls, and summarising its goal each
have a typed tool — reach for those first. Drop to HogQL only for the three
things the typed tools genuinely can't do (see
When to drop to SQL). The full $mcp_* property schema
and query recipes live in the shared reference:
models-mcp.md.
| Tool | Purpose |
| ------------------------------------------------ | ---------------------------------------------------------- |
| posthog:mcp-analytics-sessions-list | List sessions — one row per session, newest first |
| posthog:mcp-analytics-sessions-tool-calls | One session's tool calls, chronological |
| posthog:mcp-analytics-sessions-generate-intent | LLM summary of a session's goal (cached after first call) |
| posthog:execute-sql | Errored sessions, effective tool names, cross-session cuts |
The three mcp-analytics-* tools are gated behind the mcp-analytics flag and
run the same code as the sessions UI, so results match the screen. If they aren't
in your tool list, the project doesn't have the flag — fall back to
posthog:execute-sql, which is ungated.
The two detail tools default to a 7-day lookback. A session you found in a
list that reaches further back will come back empty unless you pass its
session_start as date_from:
posthog:mcp-analytics-sessions-tool-calls — date_from is an absolute ISO
timestamp; pass the session_start you got from
posthog:mcp-analytics-sessions-list.posthog:mcp-analytics-sessions-generate-intent — same date_from query
param, same reason.Empty tool calls for a session that visibly exists is almost always this, not a
data problem. Carry session_start forward from the list row.
posthog:mcp-analytics-sessions-list
{ "date_from": "-7d", "order_by": "-session_start", "limit": 100 }
Each row: session_id, tool_calls, session_start, session_end,
tools_used, mcp_client_name, distinct_id (+ resolved person_email /
person_name), and intent (empty until generated). Response is
{ results, has_next } — page with limit / offset.
Three sharp edges:
order_by takes column names, not response field names. Sort call volume
as tool_call_count (not tool_calls). duration_seconds sorts fine even
though it isn't returned. An unrecognised key silently falls back to
newest-first — so verify the order you got is the order you asked for. Valid:
session_id, session_start, session_end, duration_seconds,
tool_call_count, mcp_client_name, distinct_id; prefix - to descend.distinct_id_count is always 0. The field is in the response but the
backend never populates it, so don't read it as "one distinct id per session"
— it says nothing. To count distinct ids in a session, use SQL.search does a case-insensitive substring match across session_id,
distinct_id, mcp_client_name, and tools_used.
posthog:mcp-analytics-sessions-tool-calls
{ "id": "<session_id>", "date_from": "<session_start>", "limit": 500 }
Chronological tool_name, intent, timestamp, duration_ms, is_error,
error_message — read top to bottom to reconstruct the run. limit defaults to
500 (also the max), which is the whole page for almost every session; has_next
tells you if more remain.
Caveat: tool_name here is the raw $mcp_tool_name. Unlike the tool-quality
and tool-detail tools, this endpoint does not resolve the inner tool of a
single-exec wrapper call, so wrapper calls show the wrapper. When the inner tool
is what matters (comparing against a tool-quality ranking, tracing a specific
tool through a run), use the SQL recipe below instead. The same applies to
tools_used on the session list.
posthog:mcp-analytics-sessions-generate-intent
{ "id": "<session_id>", "date_from": "<session_start>" }
Summarises the session's recorded $mcp_intent values via an LLM and persists
the result; later calls return the cached summary. Returns
{ session_id, intent }. A 503 means LLM summarisation isn't configured — fall
back to reading the raw $mcp_intent values from the tool-call list.
Four cases, all via posthog:execute-sql, which — unlike the typed tools above —
is not gated behind the mcp-analytics flag.
1. The project doesn't have the mcp-analytics flag. The typed tools simply
won't be in your tool list. Everything below still works; this query is the
plain session listing:
SELECT
$session_id AS session_id,
min(timestamp) AS session_start,
max(timestamp) AS session_end,
dateDiff('second', min(timestamp), max(timestamp)) AS duration_seconds,
count() AS tool_calls,
countIf(toBool(properties.$mcp_is_error)) AS errors,
any(properties.$mcp_client_name) AS client
FROM events
WHERE event = '$mcp_tool_call'
AND $session_id != ''
AND timestamp >= now() - INTERVAL 7 DAY
GROUP BY session_id
ORDER BY session_start DESC
LIMIT 50
2. Errored sessions. The session list can't filter or count errors — add
HAVING errors > 0 to the query above and order by errors DESC.
3. Effective tool names within a session — the coalesce the typed tool-calls endpoint doesn't apply:
SELECT
timestamp,
coalesce(nullIf(toString(properties.$mcp_exec_tool_call_name), ''), toString(properties.$mcp_tool_name)) AS tool,
toBool(properties.$mcp_is_error) AS is_error,
toString(properties.$mcp_error_message) AS error_message,
round(toFloat(properties.$mcp_duration_ms)) AS duration_ms
FROM events
WHERE event = '$mcp_tool_call'
AND $session_id = '<session_id>'
ORDER BY timestamp ASC
4. Cross-session aggregation — "sessions per day", "sessions that used tool
X and then failed", custom breakdowns. Recipes in
models-mcp.md.
Note $session_id is a materialised events column — the same id as
$mcp_session_id. Reference it bare, never as properties.$session_id: the
properties. accessor renders null-wrapped in SELECT but as the raw column in
HAVING/ORDER, so a HAVING search would mismatch the GROUP BY key.
https://app.posthog.com/project/<project_id>/mcp-analytics/sessions$mcp_intent is only present when the client supplied it; absence is common,
so generate-intent is the more reliable goal signalexploring-mcp-tool-quality) to the
sessions that hit it, search the session list by tool name — remembering
tools_used holds raw names, so search the registered name, not the inner oneexploring-mcp-tool-usage — the front
door: routes a broad "how is my MCP doing?" question to the right toolexploring-mcp-tool-quality — error
rates and latency across all toolsexploring-mcp-intent-clusters —
group goals across many sessionsdata-ai
Signals scout for PostHog Tasks, the agent work items a project runs. Two lenses: delivery health (runs failing, clustered by repository and error class, and retry storms) every run, and on a slower rotation demand (recurring asks across human-authored tasks that point at a product gap). Skips the scout fleet's own run rows.
devops
Signals scout for the PostHog Conversations (support inbox) product. Watches the `$conversation_*` ticket-lifecycle events for support-delivery regressions — SLA breach-rate steps, first-response latency blowouts, backlog inflow-vs-resolution imbalance, and channel / assignment concentration — and files each dated regression as a report. Complements the per-ticket product-feedback signals the emission pipeline already fires; does not re-surface individual ticket content.
development
Populates and maintains a project's data catalog (semantic layer): canonical metrics, trust marks (certifications) on warehouse tables/views, and reviewed table relationships. Use when asked to set up / seed / bootstrap the data catalog or semantic layer, to catalog a project's metrics, to certify or deprecate data sources, to propose or review table joins, or to work through the proposal review queue. To *use* an existing catalog to answer a business-number question, see querying-posthog-data instead. Trigger terms: data catalog, semantic layer, canonical metric, certify table, deprecate source, relationship proposal, metric drift, review queue.
tools
Investigate logs in a PostHog project: verify a service or deployment is healthy, explain an error spike, triage an incident, or understand what a log stream is saying. Use when the user asks to "check the logs", asks whether a service, deploy, release, or change is working or broke anything, asks why errors are up or what changed, or wants the root cause of failures visible in logs. Routes the logs MCP tools (services overview, pattern mining, before/after pattern diffing, bucketed counts, facets, raw rows) so investigations start from summaries instead of raw rows or hand-written SQL over the logs table.