[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-openrouter-openrouter-analytics-query":3,"mdc--ukxbqa-key":30,"related-org-openrouter-openrouter-analytics-query":6448,"related-repo-openrouter-openrouter-analytics-query":6585},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":12,"stars":20,"repoUrl":21,"updatedAt":22,"license":23,"forks":24,"topics":25,"repo":26,"sourceUrl":28,"mdContent":29},"openrouter-analytics-query","execute analytics queries against OpenRouter","Construct and execute analytics queries against the OpenRouter API — full parameter reference for metrics, dimensions, filters, time ranges, ordering, and pagination. Use when building or debugging an analytics query, understanding the request\u002Fresponse shape, or handling query errors.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},"openrouter","OpenRouter","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fopenrouter.png","OpenRouterTeam",[13,17],{"name":14,"slug":15,"type":16},"Analytics","analytics","tag",{"name":18,"slug":19,"type":16},"API Development","api-development",187,"https:\u002F\u002Fgithub.com\u002FOpenRouterTeam\u002Fskills","2026-07-14T05:38:26.402047",null,26,[],{"repoUrl":21,"stars":20,"forks":24,"topics":27,"description":23},[],"https:\u002F\u002Fgithub.com\u002FOpenRouterTeam\u002Fskills\u002Ftree\u002FHEAD\u002Fskills\u002Fopenrouter-analytics-query","---\nname: openrouter-analytics-query\ndescription: Construct and execute analytics queries against the OpenRouter API — full parameter reference for metrics, dimensions, filters, time ranges, ordering, and pagination. Use when building or debugging an analytics query, understanding the request\u002Fresponse shape, or handling query errors.\nversion: 0.1.0\n---\n\n# OpenRouter Analytics Query Execution\n\nFull reference for constructing and executing analytics queries against the OpenRouter API.\n\n## Prerequisites\n\n- `OPENROUTER_API_KEY` must be set to a **management key**. Management keys are separate from regular API keys — get one at https:\u002F\u002Fopenrouter.ai\u002Fsettings\u002Fmanagement-keys\n\n## Query Endpoint\n\n```\nPOST https:\u002F\u002Fopenrouter.ai\u002Fapi\u002Fv1\u002Fanalytics\u002Fquery\nAuthorization: Bearer sk-or-v1-...\nContent-Type: application\u002Fjson\n```\n\nOr via the `openrouter-analytics` skill scripts:\n\n```bash\ncd \u003Copenrouter-analytics-skill-path>\u002Fscripts && npx tsx query-analytics.ts --metrics request_count\n```\n\n> **Source of truth (avoid drift):** the metric\u002Fdimension names and the request schema below are illustrative. The live, authoritative list comes from the **meta endpoint** — call `GET \u002Fapi\u002Fv1\u002Fanalytics\u002Fmeta` (or `discover-schema.ts`) and treat its response as canonical. For agent-readable docs, OpenRouter publishes [`llms.txt`](https:\u002F\u002Fopenrouter.ai\u002Fdocs\u002Fllms.txt). Prefer those over the inline examples in this file if they ever disagree.\n\n## Request Schema\n\n```json\n{\n  \"metrics\": [\"request_count\", \"total_usage\"],\n  \"dimensions\": [\"model\"],\n  \"granularity\": \"day\",\n  \"time_range\": {\n    \"start\": \"2026-05-01T00:00:00Z\",\n    \"end\": \"2026-05-20T00:00:00Z\"\n  },\n  \"filters\": [\n    { \"field\": \"model\", \"operator\": \"eq\", \"value\": \"anthropic\u002Fclaude-sonnet-4\" }\n  ],\n  \"order_by\": { \"field\": \"total_usage\", \"direction\": \"desc\" },\n  \"limit\": 100,\n  \"group_limit\": 20,\n  \"classifier_dimensions\": {\n    \"classifier_id\": \"\u003Cuuid>\",\n    \"dimension_names\": [\"category\"],\n    \"include_nulls\": false\n  },\n  \"classifier_filters\": {\n    \"classifier_id\": \"\u003Cuuid>\",\n    \"filters\": [\n      { \"field\": \"sentiment\", \"operator\": \"eq\", \"value\": \"positive\" }\n    ]\n  }\n}\n```\n\n### Required Fields\n\n| Field | Type | Description |\n|---|---|---|\n| `metrics` | `string[]` | At least one metric to compute. Call the meta endpoint to see available metrics. |\n\n### Optional Fields\n\n| Field | Type | Default | Description |\n|---|---|---|---|\n| `dimensions` | `string[]` | `[]` | Up to 2 dimensions to group by |\n| `granularity` | `string` | none | Time bucketing: `minute`, `hour`, `day`, `week`, `month` |\n| `time_range` | `object` | last 7 days | `{ start, end }` as ISO 8601 datetime strings |\n| `filters` | `object[]` | `[]` | Up to 20 filter conditions |\n| `order_by` | `object` | time desc (if granularity set) | `{ field, direction }` where field is a metric, dimension, or `\"date\"` (short-form alias — maps to `date__day`, `date__hour`, etc. based on granularity) |\n| `limit` | `integer` | 1000 | Maximum total rows to return (1–10,000). On time-series queries with dimensions and no explicit `group_limit`, the server may raise this to accommodate the expected number of time-bucket\u002Fdimension combinations. |\n| `group_limit` | `integer` | auto-computed | Maximum rows per distinct dimension combination (ClickHouse LIMIT n BY). When omitted on time-series queries (granularity + dimensions), auto-computed from the time range to guarantee full time-window coverage per group. Explicit values override the default. Ignored when no dimensions are specified. |\n| `classifier_dimensions` | `object` | none | Group by dynamic classifier-produced dimensions. See [Classifier Dimensions](#classifier-dimensions) below. |\n| `classifier_filters` | `object` | none | Filter on classifier-produced dimension values. See [Classifier Filters](#classifier-filters) below. |\n\n### Filter Object Shape\n\n```json\n{ \"field\": \"\u003Cdimension_name>\", \"operator\": \"\u003Cop>\", \"value\": \"\u003Cvalue>\" }\n```\n\n- Scalar operators (`eq`, `neq`, `gt`, `gte`, `lt`, `lte`): `value` is a string or number\n- Array operators (`in`, `not_in`): `value` is an array of strings or numbers\n- Several dimensions are **label-resolved** in query results (returned as human-readable names), but filters must use the underlying ID:\n  - `api_key_id` — numeric ID (from generation metadata) or 64-char SHA-256 hash (from `GET \u002Fapi\u002Fv1\u002Fkeys`). Hashes are auto-resolved to numeric IDs before querying.\n  - `user` — Clerk user ID (e.g. `user_abc123`), not the display name\u002Femail shown in results.\n  - `workspace` — workspace UUID, not the workspace name shown in results.\n  - `app` — numeric app ID, not the app title shown in results.\n  - `model` — permaslug (e.g. `openai\u002Fgpt-4o`), not the display name.\n- Other dimensions (`provider`, `origin`, `country`, `finish_reason`, `external_user`, etc.) are not enriched — filter values match what's returned in results.\n\n### Order By\n\n```json\n{ \"field\": \"\u003Cmetric_or_dimension_or_date>\", \"direction\": \"asc\" | \"desc\" }\n```\n\nWhen `granularity` is set and no `order_by` is specified, results are ordered by time descending.\n\n## Classifier Dimensions\n\nClassifier dimensions allow grouping by dynamic, user-defined classification labels (e.g., topic, sentiment, category) produced by a classifier attached to your account.\n\n```json\n{\n  \"classifier_dimensions\": {\n    \"classifier_id\": \"550e8400-e29b-41d4-a716-446655440000\",\n    \"dimension_names\": [\"category\"],\n    \"include_nulls\": false\n  }\n}\n```\n\n| Field | Type | Required | Description |\n|---|---|---|---|\n| `classifier_id` | `string` (UUID) | Yes | ID of the classifier (must belong to the caller's account) |\n| `dimension_names` | `string[]` | No | Specific dimension names to group by (max 10). If omitted, all classifier dimensions are included. Names must be valid identifiers (letters, digits, underscores; max 64 chars). |\n| `include_nulls` | `boolean` | No | When `true`, unclassified rows are included in results. Default `false` (only classified rows). |\n\n**Constraints:**\n- Limits the query time range to 31 days\n- Single dimension name → result column is aliased to that name (e.g., `category`)\n- Multiple dimension names → result uses generic `clf_dimension_name` \u002F `clf_dimension_value` columns\n\n## Classifier Filters\n\nClassifier filters narrow results to generations matching specific classification values. They can be used independently or alongside `classifier_dimensions`.\n\n```json\n{\n  \"classifier_filters\": {\n    \"classifier_id\": \"550e8400-e29b-41d4-a716-446655440000\",\n    \"filters\": [\n      { \"field\": \"category\", \"operator\": \"eq\", \"value\": \"billing\" },\n      { \"field\": \"sentiment\", \"operator\": \"in\", \"value\": [\"positive\", \"neutral\"] }\n    ]\n  }\n}\n```\n\n| Field | Type | Required | Description |\n|---|---|---|---|\n| `classifier_id` | `string` (UUID) | Yes | ID of the classifier (must belong to the caller's account) |\n| `filters` | `object[]` | Yes | 1–10 filter conditions on classifier dimensions |\n| `filters[].field` | `string` | Yes | Classifier dimension name to filter on |\n| `filters[].operator` | `string` | Yes | One of: `eq`, `neq`, `in`, `not_in` (no `gt`\u002F`lt` — values are strings) |\n| `filters[].value` | `string \\| string[]` | Yes | Scalar for `eq`\u002F`neq`, array for `in`\u002F`not_in` |\n\n**Constraints:**\n- Limits the query time range to 31 days\n- Only equality\u002Fset operators supported (classification values are strings — ordered comparisons would be lexicographic)\n- All filter field names must be configured dimensions on the classifier\n\n## Response Schema\n\n```json\n{\n  \"data\": {\n    \"data\": [\n      { \"date__day\": \"2026-05-19\", \"model\": \"anthropic\u002Fclaude-sonnet-4\", \"request_count\": \"1523\", \"total_usage\": 4.27 },\n      { \"date__day\": \"2026-05-18\", \"model\": \"openai\u002Fgpt-4o\", \"request_count\": \"892\", \"total_usage\": 2.15 }\n    ],\n    \"metadata\": {\n      \"query_time_ms\": 142,\n      \"row_count\": 2,\n      \"truncated\": false\n    },\n    \"cachedAt\": 1747699200000,\n    \"warnings\": [\"Could not resolve api_key_id hash: abc123...\"]\n  }\n}\n```\n\n### Response Fields\n\n| Field | Description |\n|---|---|\n| `data.data` | Array of result rows. Each row has keys for requested metrics, dimensions, and `date__\u003Cgranularity>` (when granularity is set). For `classifier_dimensions` queries with a single `dimension_name`, a column is aliased to that name (e.g., `category`). With multiple names or no `dimension_names`, rows include `clf_dimension_name` and `clf_dimension_value` columns. |\n| `data.metadata.query_time_ms` | Query execution time in milliseconds |\n| `data.metadata.row_count` | Number of rows returned |\n| `data.metadata.truncated` | `true` if results were truncated at the limit |\n| `data.cachedAt` | Unix timestamp (ms) when the result was cached. Present when the response was served from cache |\n| `data.warnings` | Optional array of non-fatal warnings (e.g., unresolvable api_key_id hashes). The query still executes normally; these inform the caller about filter resolution issues. |\n\n> **Numeric types:** Count metrics (`request_count`, `tokens_*`, etc.) are returned as strings (`\"1523\"`). Cost and rate metrics (`total_usage`, `cache_hit_rate`, latency, throughput) are returned as numbers (`4.27`). Parse count values with `Number()` or `parseInt()` before arithmetic.\n\n> **Label resolution:** Dimensions `api_key_id`, `app`, `user`, and `workspace` return human-readable labels in data rows (key names, app titles, user names, workspace names), not raw IDs.\n\n## CLI Reference\n\nThe `query-analytics.ts` script in the `openrouter-analytics` skill accepts these flags:\n\n| Flag | Description | Example |\n|---|---|---|\n| `--api-key` | API key (falls back to `OPENROUTER_API_KEY` env var) | `--api-key sk-or-v1-...` |\n| `--metrics` | Comma-separated metric names (required) | `--metrics request_count,total_usage` |\n| `--dimensions` | Comma-separated dimension names | `--dimensions model,provider` |\n| `--granularity` | Time bucket size | `--granularity day` |\n| `--start` | Time range start (ISO 8601) | `--start 2026-05-01T00:00:00Z` |\n| `--end` | Time range end (ISO 8601) | `--end 2026-05-20T00:00:00Z` |\n| `--filter-field` | Filter dimension name (first filter; see notes below) | `--filter-field model` |\n| `--filter-op` | Filter operator (first filter) | `--filter-op eq` |\n| `--filter-value` | Filter value (comma-separated for `in`\u002F`not_in`) | `--filter-value anthropic\u002Fclaude-sonnet-4` |\n| `--filter-field-N` | Dimension name for the Nth additional filter (`N` = 1–19) | `--filter-field-1 provider` |\n| `--filter-op-N` | Operator for the Nth additional filter | `--filter-op-1 eq` |\n| `--filter-value-N` | Value for the Nth additional filter | `--filter-value-1 anthropic` |\n| `--order-by` | Field to sort by | `--order-by total_usage` |\n| `--order-dir` | Sort direction | `--order-dir desc` |\n| `--limit` | Max total rows (1–10000) | `--limit 100` |\n| `--group-limit` | Max rows per dimension combination (1–10000). When omitted on time-series queries with dimensions, auto-computed server-side. | `--group-limit 50` |\n\nThe CLI prints a single JSON object to **stdout** with two keys — `data` (the result rows) and `metadata`:\n\n```json\n{\n  \"data\": [ { \"model\": \"anthropic\u002Fclaude-sonnet-4\", \"total_usage\": 4.27 } ],\n  \"metadata\": { \"query_time_ms\": 142, \"row_count\": 2, \"truncated\": false }\n}\n```\n\nA human-readable stats line (row count, query time, truncation\u002Fcache flags) is written to **stderr** for terminal use only.\n\n> **When parsing output programmatically, always check `metadata.truncated`.** If `true`, the result was capped at `--limit` and is a *partial* dataset — increase `--limit` or paginate before reporting totals\u002Frankings. Dimensions `api_key_id`, `user`, `app`, and `workspace` are already resolved to human-readable names in the data rows.\n\n**Multi-filter queries:** the CLI builds a multi-element `filters` array (ANDed together) from the unindexed base flag (`--filter-field`\u002F`--filter-op`\u002F`--filter-value`) plus the indexed `--filter-field-N`\u002F`--filter-op-N`\u002F`--filter-value-N` flags. Each filter must supply all three parts (field, op, value); a partial triplet is rejected. Up to **20 filters** total (the base flag plus indices 1–19), matching the API cap. Indices may be sparse (e.g. base + `-2` with `-1` omitted is fine — gaps are skipped, not silently dropped). For a query like `model = X AND provider = Y`:\n\n```bash\nnpx tsx query-analytics.ts --metrics request_count \\\n  --filter-field model --filter-op eq --filter-value anthropic\u002Fclaude-sonnet-4 \\\n  --filter-field-1 provider --filter-op-1 eq --filter-value-1 anthropic\n```\n\n**Flag-value caveat:** the CLI's argument parser treats any token starting with `--` as a new flag, so a filter *value* that begins with `--` cannot be passed via the CLI flags. Dimension values (model IDs, provider names, etc.) do not start with `--`, so this is rarely an issue in practice — but if you need such a value, use the [direct curl](#direct-api-usage-curl) form below instead.\n\n## Direct API Usage (curl)\n\nIf you prefer calling the API directly instead of using the scripts:\n\n```bash\ncurl -X POST https:\u002F\u002Fopenrouter.ai\u002Fapi\u002Fv1\u002Fanalytics\u002Fquery \\\n  -H \"Authorization: Bearer $OPENROUTER_API_KEY\" \\\n  -H \"Content-Type: application\u002Fjson\" \\\n  -d '{\n    \"metrics\": [\"total_usage\", \"request_count\"],\n    \"dimensions\": [\"model\"],\n    \"granularity\": \"day\",\n    \"time_range\": {\n      \"start\": \"2026-05-13T00:00:00Z\",\n      \"end\": \"2026-05-20T00:00:00Z\"\n    },\n    \"order_by\": { \"field\": \"total_usage\", \"direction\": \"desc\" },\n    \"limit\": 10,\n    \"group_limit\": 7\n  }'\n```\n\n## Query Construction Guide\n\n### Aggregates (no time series)\n\nOmit `granularity` to get a single aggregate row per dimension combination:\n\n```json\n{\n  \"metrics\": [\"total_usage\", \"request_count\"],\n  \"dimensions\": [\"model\"],\n  \"order_by\": { \"field\": \"total_usage\", \"direction\": \"desc\" },\n  \"limit\": 10\n}\n```\n\n### Time Series (with granularity)\n\nAdd `granularity` to get one row per time bucket (and per dimension combination if dimensions are set):\n\n```json\n{\n  \"metrics\": [\"request_count\"],\n  \"granularity\": \"day\",\n  \"time_range\": {\n    \"start\": \"2026-05-01T00:00:00Z\",\n    \"end\": \"2026-05-20T00:00:00Z\"\n  }\n}\n```\n\n### Filtered Queries\n\nNarrow results with filters. Multiple filters are ANDed:\n\n```json\n{\n  \"metrics\": [\"total_usage\", \"avg_latency\"],\n  \"dimensions\": [\"provider\"],\n  \"filters\": [\n    { \"field\": \"model\", \"operator\": \"eq\", \"value\": \"anthropic\u002Fclaude-sonnet-4\" }\n  ]\n}\n```\n\n### Multi-Dimension Queries\n\nCombine up to 2 dimensions for cross-tabulation:\n\n```json\n{\n  \"metrics\": [\"request_count\"],\n  \"dimensions\": [\"model\", \"provider\"],\n  \"order_by\": { \"field\": \"request_count\", \"direction\": \"desc\" },\n  \"limit\": 20\n}\n```\n\n## Error Handling\n\n| Status | Meaning | Action |\n|---|---|---|\n| 400 | Invalid query (bad metric name, too many dimensions, invalid time range) | Check the meta endpoint for valid values. Verify time range start \u003C end. Max 2 dimensions, 20 filters. |\n| 401 | Invalid or missing API key | Check `OPENROUTER_API_KEY` is set correctly |\n| 403 | Not a management key | The key must be a provisioning\u002Fmanagement key. Create one at openrouter.ai\u002Fsettings\u002Fmanagement-keys |\n| 408 | Query timed out | Narrow the time range, reduce dimensions, or add filters to scan less data |\n| 429 | Rate limited (64 RPM) | Wait and retry |\n| 500 | Server error | Retry after a moment |\n\n## Time Range Behavior\n\nSome metric\u002Fdimension combinations support time ranges up to **365 days** (with daily granularity), while others are limited to **31 days**. 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Also use alongside openrouter-models when the user asks what model should power an app, product, workflow, or use case and benchmark evidence could inform or rule out part of the recommendation, including creative writing, editing, coding, design, agentic, or intelligence-heavy apps. Do not use for OpenRouter usage analytics, billing\u002Fspend analysis, generation metadata, provider uptime\u002Flatency, generic model pricing\u002Fcapability lookup without any selection or benchmark-relevance decision, or creating an evaluation suite for a local app.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[6536,6537,6540],{"name":14,"slug":15,"type":16},{"name":6538,"slug":6539,"type":16},"Benchmarking","benchmarking",{"name":6488,"slug":6489,"type":16},"2026-07-14T05:38:27.658475",{"slug":6543,"name":6543,"fn":6544,"description":6545,"org":6546,"tags":6547,"stars":20,"repoUrl":21,"updatedAt":6550},"openrouter-generations","retrieve metadata for OpenRouter generations","Retrieve detailed metadata and stored content for individual OpenRouter generations. Use when the user wants to inspect a specific request — its cost, latency, token usage, provider routing, or the actual prompt\u002Fcompletion text — or is debugging a failed or unexpected generation.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[6548,6549],{"name":6488,"slug":6489,"type":16},{"name":9,"slug":8,"type":16},"2026-07-14T05:38:25.132801",{"slug":6552,"name":6552,"fn":6553,"description":6554,"org":6555,"tags":6556,"stars":20,"repoUrl":21,"updatedAt":6561},"openrouter-images","generate images with OpenRouter","Generate images from text prompts and edit existing images using OpenRouter's dedicated Image API. Use when the user asks to create, generate, or make an image, picture, or illustration from a description, or wants to edit, modify, transform, or alter an existing image with a text prompt.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[6557,6560],{"name":6558,"slug":6559,"type":16},"Image Generation","image-generation",{"name":9,"slug":8,"type":16},"2026-07-14T05:38:21.393411",{"slug":6563,"name":6563,"fn":6564,"description":6565,"org":6566,"tags":6567,"stars":20,"repoUrl":21,"updatedAt":6570},"openrouter-models","query OpenRouter model metadata and pricing","Query OpenRouter for available AI models, pricing, capabilities, throughput, and provider performance. Use when the user asks about available OpenRouter models, model pricing, model context lengths, model capabilities, provider latency or uptime, throughput limits, supported parameters, wants to search\u002Ffilter\u002Fcompare models, or find the fastest provider for a model.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[6568,6569],{"name":6488,"slug":6489,"type":16},{"name":9,"slug":8,"type":16},"2026-07-14T05:38:22.650307",{"slug":6572,"name":6572,"fn":6573,"description":6574,"org":6575,"tags":6576,"stars":20,"repoUrl":21,"updatedAt":6584},"openrouter-oauth","implement OpenRouter OAuth authentication","Implement \"Sign In with OpenRouter\" using OAuth PKCE — framework-agnostic, no SDK or client registration required. Use when the user wants to add OpenRouter login, authentication, sign-in buttons, OAuth, or AI model inference API keys for browser-based apps. No client registration, no backend, no secrets required.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[6577,6580,6583],{"name":6578,"slug":6579,"type":16},"Auth","auth",{"name":6581,"slug":6582,"type":16},"OAuth","oauth",{"name":9,"slug":8,"type":16},"2026-07-14T05:38:20.116308",{"items":6586,"total":897},[6587,6594,6600,6606,6612,6617,6622],{"slug":6451,"name":6451,"fn":6452,"description":6453,"org":6588,"tags":6589,"stars":20,"repoUrl":21,"updatedAt":6466},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[6590,6591,6592,6593],{"name":6457,"slug":6458,"type":16},{"name":6460,"slug":6461,"type":16},{"name":9,"slug":8,"type":16},{"name":6464,"slug":6465,"type":16},{"slug":6468,"name":6468,"fn":6469,"description":6470,"org":6595,"tags":6596,"stars":20,"repoUrl":21,"updatedAt":6476},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[6597,6598,6599],{"name":6457,"slug":6458,"type":16},{"name":6460,"slug":6461,"type":16},{"name":6464,"slug":6465,"type":16},{"slug":6478,"name":6478,"fn":6479,"description":6480,"org":6601,"tags":6602,"stars":20,"repoUrl":21,"updatedAt":6490},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[6603,6604,6605],{"name":18,"slug":19,"type":16},{"name":6485,"slug":6486,"type":16},{"name":6488,"slug":6489,"type":16},{"slug":6492,"name":6492,"fn":6493,"description":6494,"org":6607,"tags":6608,"stars":20,"repoUrl":21,"updatedAt":6504},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[6609,6610,6611],{"name":6498,"slug":6499,"type":16},{"name":6501,"slug":6502,"type":16},{"name":6464,"slug":6465,"type":16},{"slug":119,"name":119,"fn":6506,"description":6507,"org":6613,"tags":6614,"stars":20,"repoUrl":21,"updatedAt":6512},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[6615,6616],{"name":14,"slug":15,"type":16},{"name":9,"slug":8,"type":16},{"slug":4,"name":4,"fn":5,"description":6,"org":6618,"tags":6619,"stars":20,"repoUrl":21,"updatedAt":22},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[6620,6621],{"name":14,"slug":15,"type":16},{"name":18,"slug":19,"type":16},{"slug":6519,"name":6519,"fn":6520,"description":6521,"org":6623,"tags":6624,"stars":20,"repoUrl":21,"updatedAt":6529},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[6625,6626,6627],{"name":14,"slug":15,"type":16},{"name":6488,"slug":6489,"type":16},{"name":6527,"slug":6528,"type":16}]