posthog

Plugin posthog from marketplace pleaseai in pleaseai/claude-code-plugins. Commands read from the repo's manifest — today.

Skills (188)

• adding-warehouse-person-properties

  Sync columns from a synced data warehouse table onto PostHog person or group properties, so warehouse data becomes usable anywhere person and group properties already work: feature flag targeting, cohorts, insight filters and breakdowns, surveys, session replay filters, workflows, and the person pro

• analyzing-ai-citations

  Answer AI citation and answer engine optimization (AEO) questions in PostHog: whether AI answer engines (ChatGPT, Claude, and an Exa retrieval baseline) cite the project's site for its tracked prompts, which topics and engines cite it least, which domains get cited instead, and whether citations lin

• analyzing-expensive-users

  Analyze the most expensive users in AI observability and explain why they cost so much. Use when the user asks about top spenders, expensive users, per-user LLM cost, user-level cost drivers, or patterns behind high AI observability spend.

• analyzing-experiment-session-replays

  Analyze session replay patterns across experiment variants to understand user behavior differences. Use when the user wants to see how users interact with different experiment variants, identify usability issues, compare behavior patterns between control and test groups, or get qualitative insights

• analyzing-funnel-correlation

  Find the events and person properties that correlate with funnel conversion or drop-off. Use when the user asks why people convert or drop off in a funnel, what converters do differently, which events or properties predict success or failure, or asks for "correlation analysis" on a funnel. Computes

• analyzing-offline-evaluations

  Inspect and compare offline AI evaluation experiments, diagnose case-level regressions, and follow scorer history across application, model, or prompt changes. Use when a user asks whether an offline run improved, why a case failed, how scores changed between runs, or how to publish externally compu

• analyzing-task-runs

  Split a completed PostHog task run into activity records — what the agent tried, whether it worked, what blocked it — and record each one through the report_activity tool. Use when a task asks to analyze a run, produce a task analysis, or review a run from an attached run log. Covers the log query p

• assessing-heatmaps

  Assesses what a page's heatmap is telling you and recommends concrete changes. Pulls click / rageclick / scroll-depth data for a URL, names the hot elements by cross-referencing autocapture events on the same page, and can create a saved heatmap the user opens in PostHog, then summarizes the behavio

• auditing-endpoints

  Audit every endpoint in a PostHog project for staleness, failed materialisations, and unused materialised versions. Use when the user asks "what endpoints can I clean up?", "are any of my endpoints broken?", "which materialised versions are still being called?", or wants a one-shot cleanup pass over

• auditing-experiments-flags

  Audit PostHog experiments and feature flags for configuration issues, staleness, and best-practice violations. Read when the user asks to audit, health-check, or review experiments or feature flags, check flag hygiene, or verify experiment setup.

• auditing-warehouse-source-health

  Audit the health of a PostHog project's data warehouse sources and syncs — find every broken or degraded source connection, sync schema, and webhook channel. Use when the user asks "why are my imports failing?", "what's broken with my sources?", "why is my warehouse data stale?", or wants a one-shot

• auditing-warehouse-view-health

  Audit the health of a PostHog project's materialized views (saved queries) — find every failed materialization and flag unused or stale materialized views that cost storage and compute. Use when the user asks "which of my views are broken?", "why is this materialized view failing?", "are any of my v

• authoring-data-quality-checks

  Adds and runs data quality checks (dbt-test style assertions) on a project's warehouse tables and saved-query views, and HogQL catalog metrics: not-null, uniqueness, accepted values, referential integrity, row-count bounds, freshness, and custom HogQL. Metrics support custom SQL checks only. Use whe

• authoring-error-tracking-alerts

  Author error tracking alerts that fire when an issue is created, reopened, or starts spiking. Use when the user asks to set up error notifications, route exceptions to Slack/webhook/Linear, or evaluate which error events are worth alerting on. Covers trigger-event selection, integration choice, dedu

• authoring-insight-alerts

  Author insight alerts that notify when a trends, SQL, or funnel insight crosses a bound, changes sharply, or looks anomalous. Use when the user asks to alert on a metric or insight, get notified when a number drops or spikes, set up anomaly detection, or use the AI anomaly detector (the llm detector

• authoring-log-alerts

  Author useful, low-noise log alerts on services in a PostHog project. Use when the user asks to set up alerts for their logs, suggest alerts they should add, or evaluate whether a service is worth monitoring. Covers service triage, baseline characterisation, threshold drafting, back-testing via simu

• authoring-scouts

  Write, edit, and adapt PostHog Signals scouts: scheduled agents that scan a project and report findings. Use to change a canonical scout's scope, thresholds, schedule, or dry-run settings; add a scout for an uncovered surface; record structured output from scheduled LLM scoring; or give feedback thr

• building-a-dashboard

  Build a new dashboard, or update an existing one, from a set of insights — the same job the in-app assistant does with its upsert-dashboard tool, but over MCP. Use when a user asks to create a dashboard, put several metrics/charts together on one page, assemble a dashboard for a topic (product analy

• building-canvases

  Create or edit a PostHog freeform canvas — a sandboxed browser application (data board, document, form, small tool, graphics experiment) stored in PostHog and rendered by the desktop/web app. Use when a task asks to build, generate, update, or fix a standalone canvas app, or when a freeform canvas i

• building-html-canvases

  Author a PostHog canvas with semantic HTML, CSS, and direct browser APIs — documents, articles, generative graphics, 2D canvas and WebGL experiences, and focused experiments where React components add no useful structure. Use after building-canvases has routed a canvas request to a plain-HTML/browse

• building-loops

  Build a Loop for PostHog Desktop: a workflow that creates an AI task each time its trigger fires, optionally followed by a Slack or email notification with the task's result. Use when asked to create, set up, or change a loop, a recurring agent, a scheduled task, or an automation that runs an AI tas

• building-react-quill-canvases

  Author the React + Quill implementation of a PostHog canvas: the single-component contract, the allowed imports, Quill (PostHog's design system) component and composition rules, theme-aware design tokens, loading skeletons, and the in-canvas date picker. Use after building-canvases has routed a canv

• building-workflows

  Build, edit, test, enable, and monitor PostHog workflows over MCP. Author the action/edge graph so it runs and opens cleanly in the visual editor, then change drafts surgically with patch operations. Use when asked to build, set up, automate, change, fix, or debug a workflow, campaign, broadcast, dr

• checking-deploy-timing

  Determine when a PostHog code change reached a given environment by reading the hidden GIT deploy annotations in the project and correlating them with the merge commit on GitHub. Use when PostHog staff ask "when was X deployed", "is my change live in the US/EU yet", "has my PR shipped", "did the fix

• checking-member-access

  Explains what a member or a role can do in a PostHog project, using the access control MCP tools. Use when the user asks what someone can see or edit, who can edit dashboards or feature flags, why a member can or cannot open a dashboard, notebook or table, what a role grants, which properties are hi

• choosing-trend-or-slope-view

  Clarify how to visualize change over a time range before building a trend. Use whenever the user asks how much something changed, grew, dropped, improved, or regressed between two points or periods — "how much did X change from A to B", "before vs after", "start vs end", "week over week", "compare t

• cleaning-up-stale-feature-flags

  Identify stale feature flags in a PostHog project and clean up the code that checks them. Use when the user wants to find, audit, or remove unused, fully rolled out, or abandoned feature flags, run a feature flag hygiene review or a weekly cleanup, reduce feature flag tech debt, or asks "which flags

• composing-grid-canvases

  Compose PostHog grid canvases — widget grids (including the user's home canvas) built from reusable component canvases. Use when a task asks to add, fill, move, resize, or remove a widget on a grid or home canvas, to compose a whole canvas of widgets from one ask, to build a reusable widget/componen

• configuring-experiment-analytics

  Configures the analytics side of a PostHog experiment — exposure criteria (server-resolved default exposure event vs custom exposure events), primary and secondary metrics, the supported metric types (count, sum, ratio with `math` and `math_property`, retention with `retention_window_start` and `sta

• configuring-experiment-rollout

  Configures the rollout shape of a PostHog experiment — the variant split (50/50, 80/20, A/B/C ratios), the overall rollout percentage that gates how many users enter the experiment, and the disambiguation when a percentage like "roll out to 25%" could mean either. Use when the user mentions a rollou

• consuming-endpoints-from-client-code

  Wire a PostHog endpoint into a client app or SDK. Covers fetching the OpenAPI spec, generating a typed client with openapi-generator or @hey-api/openapi-ts, sending the right auth header, shaping the variables payload (HogQL code_name vs insight breakdown property), handling rate-limit and materiali

• context-layer-consolidation

  Keep the context wiki coherent using the deterministic lint report queue

• context-layer-dreaming

  Synthesizes recent organizational activity into a durable context wiki. Use when running a nightly or incremental context-layer dream, or when updating sourced organizational context from completed work.

• context-layer-health-check

  Reviews context wiki quality after deterministic consolidation. Use when recent wiki-miss entries, contradictory or unsupported claims, stale priorities, near-duplicate subjects, or concepts without an owning page need semantic triage.

• copying-endpoints-across-projects

  Copy a PostHog endpoint (a saved HogQL/insight query exposed as an API route) to another project in the same organization, or duplicate it under a new name in the same project. Use when the user wants to duplicate an endpoint, promote an endpoint from staging to production, replicate an endpoint's q

• copying-flags-across-projects

  Copy a feature flag from one PostHog project to one or more target projects in the same organization. Use when the user wants to duplicate a flag, promote a flag from staging to production, sync flags across projects, or replicate a flag configuration in a different workspace. Covers cohort remappin

• creating-ai-subscription

  Create a recurring AI-generated PostHog report — schedule a free-text prompt to run on a cron, with the LLM-synthesized markdown delivered to email, Slack, or Microsoft Teams on each tick. Use when the user wants a recurring AI summary of X on any cadence (daily, weekly, monthly, yearly) rather than

• creating-an-endpoint

  Create a PostHog endpoint with the right shape on the first try — covers query kind choice, name conventions, what to expose as variables (HogQL code_name vs insight breakdown), data_freshness_seconds, and whether to materialise on day one. Use when the user says "create an endpoint", "expose this q

• creating-box-plot-insights

  Creates product analytics or SQL-backed box plot insights in PostHog. Use when a user asks to create, build, or save a box plot, visualize a numeric distribution, compare quartiles or medians across dates or groups, or turn SQL results into a box plot. Chooses between a standard Trends box plot and

• creating-experiments

  Guides agents through experiment creation: reading the project's setup with experiment-setup-context, defining the hypothesis, configuring rollout and bucketing, setting up analytics and running time, and reporting which choices are guesses. Delegates rollout decisions to configuring-experiment-roll

• creating-online-evaluations

  Author continuously-running online evaluations in PostHog AI observability, grounded in real failure modes you've identified. Use when the user wants evaluations that automatically score new generations or whole traces going forward — "create an eval to catch X", "continuously check that responses d

• creating-replay-vision-scanners

  Guides agents through creating and safely sizing a Replay Vision scanner: choosing the scanner type (monitor/classifier/scorer/summarizer), shaping the RecordingsQuery that selects sessions, and — crucially — estimating the credits it will spend and checking the org's remaining budget before creatin

• creating-surveys

  Creates and launches PostHog surveys through MCP, including NPS/CSAT popovers, hosted feedback forms, and headless surveys. Guides survey type selection, audience targeting, draft review, and launch readiness. Use when asked to create a survey or form, or before calling survey-create. For investigat

• debugging-experiments

  Debug and support PostHog Experiments (A/B tests) for a customer looking at their own results. Use whenever an experiment support ticket is pasted or a customer asks a results question, most commonly "why aren't my exposures even?", "why is one variant getting no traffic?", "why am I missing / seein

• debugging-failed-data-quality-checks

  Finds out why a data quality check failed or errored, looks at the rows it matched, and recommends the fix. Also covers a materialized view refresh that the data quality gate did not publish. Use when asked why a check is red, what rows failed, why a view shows "Not published", why a view's data is

• debugging-surveys

  Diagnose PostHog Surveys configuration and responses across all five SDKs (web/posthog-js, iOS, Android, Flutter, React Native). Use whenever a Surveys support ticket is pasted ("survey not showing", "fewer responses than expected", "responses disappeared", "responses are incomplete", "only the firs

• designing-email-templates

  Author, save, and edit email templates in the PostHog workflows library — compose email design JSON with Liquid personalization and create and round-trip-edit templates over MCP. Use when asked to design, build, update, or fix an email template for workflows, broadcasts, or campaigns.

• designing-replay-vision-scanners

  Designs a Replay Vision scanner that produces trustworthy observations: one visible question per scanner, a type chosen from the answer shape, a query that selects only sessions able to answer it, a prompt that demands on-screen proof and allows no or inconclusive, a model picked by the cost of a wr

• diagnosing-ci-and-merge-bottlenecks

  Diagnoses CI and pull request pipeline health for a GitHub repo with the engineering analytics MCP tools: pull-requests, workflow-health, pr-lifecycle, engineering-analytics-flaky-tests, engineering-analytics-team-ci-health, and the CI cost tools. Use when asked whether CI is getting faster or slowe

• diagnosing-endpoint-performance

  Diagnose why a PostHog endpoint is slow or expensive and propose a concrete fix — bump the cache TTL, enable materialisation, restructure variables, or rewrite the query. Use when the user says "this endpoint is slow", "my endpoint times out", "we're hitting the cost cap on this one", or asks "shoul

• diagnosing-experiment-health

  Runs diagnostics and a health check on one PostHog experiment: its setup, exposures, results and changes during the run. Covers 0 exposures, sample ratio mismatch, lost or uneven exposures, users in multiple variants, identity faults, who the experiment counts, significance traps (peeking, A/A, 'tar

• diagnosing-failed-warehouse-syncs

  Diagnose why a data warehouse sync is failing and recommend the right recovery action. Use when the user asks "why isn't my Stripe/Postgres/Hubspot sync working?", "this table has been stuck for hours", "the data in the warehouse looks wrong", or wants to troubleshoot a specific source or schema. Co

• diagnosing-missing-recordings

  Diagnoses why a session recording is missing or was not captured. Use when a user asks why a session has no replay, why recordings aren't appearing, or wants to troubleshoot session replay capture issues for a specific session ID or across their project. Covers SDK diagnostic signals, project settin

• diagnosing-sdk-health

  Diagnoses the health of a project's PostHog SDK integrations — which SDKs are out of date and how to fix them. Use when a user asks about PostHog SDK versions, outdated SDKs, upgrade recommendations, "SDK health", "SDK doctor" (the former name), or when events or features seem off and it might be du

• diagnosing-stacktrace-symbolication

  Help users debug PostHog Error Tracking stack-trace symbolication for any supported platform — JavaScript/TypeScript web, React Native (Hermes), Android (Proguard / R8), or iOS / macOS (dSYM). The PostHog symbol-set lookup flow is universal across platforms; build-tool and artifact details live in p

• downloading-batch-export-files

  Export PostHog events, persons, sessions, or the results of a HogQL query on demand and download the resulting files. Use when the user asks to download/export raw PostHog data, export HogQL query results, create a one-off file export, fetch a Parquet or JSONLines export, or use the file_download_ba

• exploring-ai-failures

  Find where an AI/LLM application is failing in production and surface the failure patterns, working from real traces. Use when someone wants to understand what's going wrong with an AI feature, find and categorize failure modes, triage errors, or investigate quality issues (wrong answers, ignored in

• exploring-apm-traces

  Investigates distributed application performance using PostHog APM (OpenTelemetry span) data via MCP. Use when the user asks about service traces, slow HTTP/database spans, error spans, error-rate trends or spikes, latency distributions, trace IDs, or span attributes — not AI observability traces or

• exploring-autocapture-events

  Guides exploration of $autocapture events captured by posthog-js to understand user interactions, find CSS selectors (especially data-attr attributes), evaluate selector uniqueness, query matching clicks ad-hoc, and create actions. Use when the user asks about autocapture data, wants to find what us

• exploring-endpoint-execution-logs

  Explore and diagnose a PostHog endpoint's execution logs — error messages, failed runs, cache misses, slow runs, or unexpected row counts during endpoint invocations. Use when the user says "my endpoint is failing", "show me the logs for endpoint X", "what error did endpoint Y produce", "why did end

• exploring-live-traffic

  Inspects PostHog Web analytics Live tab data — current users online, last-30-minutes pageviews, top pages, referrers, devices, browsers, countries, bot traffic, and the per-minute bot/users charts. Use when the user asks "who is on my site right now?", "what is happening live?", "what bots are crawl

• exploring-llm-clusters

  Investigate AI observability clusters — understand usage patterns in AI/LLM traffic, compare cluster behavior, compute cost/latency metrics, and drill into individual traces within clusters.

• exploring-llm-costs

  Investigate LLM spend in PostHog — total cost over time, cost by model, provider, user, trace, or custom dimension, token and cache-hit economics, and cost regressions. Use when the user asks "how much are we spending on LLMs?", "which model / user / feature is most expensive?", "why did cost spike?

• exploring-llm-evaluations

  Investigate AI observability evaluations — `hog` (deterministic code-based), `llm_judge` (LLM-prompt-based), and `sentiment` (user-message sentiment). Find existing evaluations, inspect their configuration, run them against specific generations, query individual results, and set up scheduled reports

• exploring-llm-traces

  Debug and inspect LLM/AI agent traces using PostHog's MCP tools. Use when the user pastes a trace or session URL (e.g. /ai-observability/traces/<id> or /ai-observability/sessions/<id>), asks to debug a trace, figure out what went wrong, check if an agent used a tool correctly, verify context/files w

• exploring-mcp-intent-clusters

  Explore PostHog MCP intent clusters — agent goals grouped by semantic similarity, with each cluster's tool distribution and error rates, plus the tool-centric pivot (capture rate per intent, discovery rate against the advertised catalog, description fit, tool overlaps). Use when the user asks "what

• exploring-mcp-sessions

  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 ha

• exploring-mcp-tool-original-user-motive

  Build a starting-point taxonomy for an MCP tool — what users were trying to accomplish before they reached the tool — and publish it as a PostHog notebook. Reconstructs each session's goal from its opening tool calls, then clusters those goals into named categories with size, share, and facet mix. U

• exploring-mcp-tool-quality

  Investigate the quality of PostHog MCP tool calls — error rates, latency, reach, and which tools are failing or slow. Use when the user asks "which MCP tool has the highest error rate?", "what's the slowest tool?", "which tools fail most often?", "how reliable is tool X?", wants a tool-quality matri

• exploring-mcp-tool-usage

  Starting point for exploring how a PostHog MCP server's tools are used — routes a broad question to the typed tool that answers it. Use when the user asks "how is my MCP doing?", "what should I look at?", "explore my tool calls", "who uses my MCP tools?", "what are agents doing with the MCP?", or pa

• exploring-replay-vision-observations

  Guides agents through pulling a Replay Vision scanner's observations, reading the findings, and acting on them — summarizing patterns across sessions, drilling into individual recordings, and turning real, corroborated issues into PostHog tasks, insights, or an investigating-replay hand-off.\nTRIGGE

• exploring-scouts

  How to explore and make sense of PostHog Signals scouts — the scheduled agents that scan a project and write reports into the Signals inbox. Use when a user wants to understand what scouts they have, how each one is behaving, and whether the fleet is actually working. Covers surveying the fleet and

• feature-usage-feed

  Set up an LLM-judge evaluation that extracts canonical use cases for a PostHog feature at scale and streams the results to a Slack channel as a live feed. Use when someone wants to understand how users are actually using a specific AI/LLM-powered feature in production — what they're investigating, w

• filtering-bot-traffic

  Identify, measure, and exclude bot / crawler / AI-agent traffic in PostHog web and product analytics using the traffic classification surface (the isLikelyBot / getTrafficType HogQL functions and the $virt_* virtual properties). Use when the user asks to "exclude bots", "filter out crawlers", "remov

• finding-deleted-feature-flags

  Find feature flags that were soft-deleted in the active project within a recent time window. Use when the user asks "what flags were deleted in the last N days", "show me recently deleted feature flags", "who deleted flag X", "audit recent flag deletions", or anything similar. Handles the non-obviou

• finding-experiments

  Resolves a PostHog experiment reference from natural language to a concrete experiment ID by browsing `experiment-list` (not feature-flag tools), with disambiguation when multiple experiments match. Use when the user names or quotes an experiment ("split test demo", "the File engagement boost experi

• finding-replay-for-issue
• finding-sessions-to-watch
• formatting-insight-axes
• grouping-noisy-errors
• implementing-api-surveys
• importing-push-tokens
• inbox-exploration
• installing-posthog-from-chat
• installing-posthog-in-a-codebase
• instrument-error-tracking
• instrument-feature-flags
• instrument-integration
• instrument-llm-analytics
• instrument-logs
• instrument-metrics
• instrument-product-analytics
• instrument-tracing
• investigate-metric
• investigating-ci-failures
• investigating-error-issue
• investigating-logs
• investigating-metric-anomalies
• investigating-replay
• linking-errors-to-traces
• managing-endpoint-versions
• managing-experiment-lifecycle
• managing-llm-prompts
• managing-path-cleaning-rules
• managing-reminders
• managing-self-driving-spend
• managing-streamlit-apps
• managing-subscriptions
• migrating-from-customer-io
• migrating-from-fivetran
• modeling-activation-metrics
• modeling-conversion-metrics
• modeling-dimension-tables
• modeling-product-usage-metrics
• modeling-revenue-metrics
• modeling-warehouse-foundations
• prioritizing-my-inbox
• querying-canvas-data
• querying-posthog-data
• resolving-ingestion-warnings
• review-hog-authoring
• review-hog-blind-spots-general
• review-hog-perspective-contracts-security
• review-hog-perspective-logic-correctness
• review-hog-perspective-performance-reliability
• review-hog-resolution-criteria-gaps
• review-hog-resolution-criteria-small
• review-hog-resolution-criteria
• review-hog-validation-criteria
• reviewing-warehouse-suggestions
• scanning-experiments-with-replay-vision
• sending-transactional-emails
• setting-up-a-custom-rest-source
• setting-up-a-data-warehouse-source
• setting-up-data-catalog
• setting-up-supabase-auth-emails
• setting-up-warehouse-properties
• signals-scout-ai-observability
• signals-scout-anomaly-detection
• signals-scout-apm
• signals-scout-conversations
• signals-scout-csp-violations
• signals-scout-customer-analytics-billing-and-usage
• signals-scout-customer-analytics
• signals-scout-data-pipelines
• signals-scout-data-warehouse
• signals-scout-error-tracking
• signals-scout-experiments
• signals-scout-feature-flags
• signals-scout-first-report
• signals-scout-general
• signals-scout-health-checks
• signals-scout-inbox-validation
• signals-scout-insight-alerts
• signals-scout-logs
• signals-scout-mcp-tool-calls
• signals-scout-observability-gaps
• signals-scout-pr-follow-up
• signals-scout-product-analytics
• signals-scout-replay-vision
• signals-scout-revenue-analytics
• signals-scout-session-replay
• signals-scout-skills-store
• signals-scout-surveys
• signals-scout-tasks
• signals-scout-unused-features
• signals-scout-web-analytics
• signals-scout-web-vitals
• signals-scout-workflows
• signals
• skills-store
• suggesting-data-imports
• suggesting-path-cleaning-rules
• suppressing-noisy-errors
• syncing-migrated-self-managed-tables
• transcribing-slack-audio
• triaging-error-issues
• triaging-visual-review-runs
• tuning-incremental-sync-config
• turning-engineering-analytics-into-insights
• understanding-billing-usage
• validating-and-publishing-canvases
• working-with-autoresearch
• working-with-scouts
• working-with-skills
• working-with-task-comments
• writing-simplified-technical-english
• writing-streamlit-apps

Slash commands (3)

• /posthog:llma-cc-ingest

  Manually send a Claude Code session log to PostHog LLM Analytics

• /posthog:llma-cc-setup

  Set up PostHog LLM Analytics to capture Claude Code sessions

• /posthog:llma-cc-status

  Check if Claude Code sessions are being sent to PostHog LLM Analytics

Subagents (1)

• error-analyzer

  Analyze multiple PostHog errors in parallel to identify patterns, root causes, and prioritize fixes based on user impact.

MCP servers (1)

• posthog

  connects to: https://mcp.posthog.com/mcp

Hooks (3)

• PostToolUse

  "${CLAUDE_PLUGIN_ROOT:-$PLUGIN_ROOT}/hooks/skill-invoked.sh"

• SessionEnd

  python3 "${CLAUDE_PLUGIN_ROOT:-$PLUGIN_ROOT}/telemetry/hooks/session-end-llma.py"

• PreToolUse

  "${CLAUDE_PLUGIN_ROOT:-$PLUGIN_ROOT}/hooks/gate-exec-write.sh"

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