[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-cline-vibe-prospecting":3,"mdc--lbsz2o-key":36,"related-repo-cline-vibe-prospecting":3892,"related-org-cline-vibe-prospecting":4015},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":25,"repoUrl":26,"updatedAt":27,"license":28,"forks":29,"topics":30,"repo":31,"sourceUrl":34,"mdContent":35},"vibe-prospecting","research companies and contacts for prospecting","Find company & contact data. Turn your agent into a prospecting platform. Get contact information, roles, tech stack, business events, website changes, intent data. Build lead lists, research prospects, identify talent. 150M+ companies, 800M+ professionals, 50+ data sources.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"cline","Cline","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fcline.png",[12,16,19,22],{"name":13,"slug":14,"type":15},"Research","research","tag",{"name":17,"slug":18,"type":15},"Prospecting","prospecting",{"name":20,"slug":21,"type":15},"Sales","sales",{"name":23,"slug":24,"type":15},"Lead Enrichment","lead-enrichment",10,"https:\u002F\u002Fgithub.com\u002Fcline\u002Fskills","2026-07-12T08:13:48.374789",null,4,[],{"repoUrl":26,"stars":25,"forks":29,"topics":32,"description":33},[],"A collection of skills used at Cline","https:\u002F\u002Fgithub.com\u002Fcline\u002Fskills\u002Ftree\u002FHEAD\u002Fskills\u002Fvibe-prospecting","---\nname: \"vibe-prospecting\"\ndescription: \"Find company & contact data. Turn your agent into a prospecting platform. Get contact information, roles, tech stack, business events, website changes, intent data. Build lead lists, research prospects, identify talent. 150M+ companies, 800M+ professionals, 50+ data sources.\"\ncompatibility: Run with `npx @vibeprospecting\u002Fvpai@latest`. If the CLI does not work and the user's agent environment supports connectors, suggest the Vibe Prospecting connector to the user.\nmetadata:\n  version: \"0.1.62\"\n---\n\n# Vibe Prospecting CLI\n\nUse the CLI: `npx @vibeprospecting\u002Fvpai@latest`. Treat every tool response as JSON.\n\n**Cowork mode: always use this connector flow.** Before doing any work in Cowork mode, check whether the Vibe Prospecting MCP connector tools are available in your tool list (look for a tool matching the pattern `mcp__*__fetch-entities`).\n\nIf those tools are present, use the connector directly and follow its tool descriptions and schemas. If those tools are NOT present:\n1. Call `mcp__mcp-registry__search_mcp_registry` with keywords `[\"vibe prospecting\", \"explorium\"]`\n2. Call `mcp__mcp-registry__suggest_connectors` with the UUID `1bdcb159-b6f0-4f13-bc08-fdb40b007828` and keywords `[\"prospecting\"]`\n3. Tell the user to click **Connect** on the card — the tools unlock automatically once authorized\n4. **Poll until connected.** On every subsequent turn, re-check your tool list for `mcp__*__fetch-entities`. Do not start prospecting work until those tools appear. **Never** fall back to the CLI, the npm `vpai` tool, or an OAuth URL in Cowork mode — the Cowork connector store is the only path. If the user cannot connect from the suggested card, tell them to open the **connector store** and install Vibe Prospecting from there, then poll again. If tools are still missing, remind the user to connect and wait; repeat until the connector is available.\n\n**If the CLI does not work** outside Cowork mode (e.g. `npx` unavailable, sandboxed environment, permission denied), and the user's agent environment supports connectors, suggest the Vibe Prospecting connector to the user. The rest of this file is CLI-only. In Cowork mode, use the connector store flow above.\n\n## Hard Rules\n\n1. **Sample first, always.** Run the COMPLETE workflow on exactly 5 entities (`--number-of-results 5`) before any full run. That cap is a **quality gate only**: Explorium can match **many more** rows for the same filters. **Never** describe those 5 rows as the full dataset, \"all results,\" or \"what the database has.\" Show the sample, state clearly that it is a preview and the index has more, then after explicit approval **re-run the same CLI tool(s)** you used in the sample chain with full-scale parameters (same `--args`, session, and filters; raise caps such as **`--number-of-results`** to the user's real target where that flag applies). Run **`fetch-entities-statistics`** only when **all** of your discovery **`fetch-entities`** filters (and any supported scope flags) are valid for statistics too — see rule 8. Never auto-export. \"Find 100\" still means sample 5 first, then scale up after approval.\n2. **`--tool-reasoning '\u003Cuser wording>'`** on every real call. Use the user's request verbatim. Reuse across the whole workflow. Skip ONLY when running `\u003Ctool> --all-parameters` with no `--args`.\n3. **Chain via session DB, never paste IDs.** Each step prints `session_id`, `db_path`, and `table_name`. Pass **`--session-id`** with the **`session_id`** from the prior JSON output so the next command uses the same SQLite session store. With **`--session-id`**, **`--table-name`** is **required** for **`enrich-business`**, **`enrich-prospects`**, **`fetch-businesses-events`**, and **`fetch-prospects-events`** — pass the prior step's **`table_name`** exactly. For **`match-*`** only, **`--table-name`** is optional (CLI can pick the first table with the right ID column when omitted). For **`fetch-entities`** prospects scoped to earlier companies, use **`--businesses-table-name`** plus **`--session-id`**.\n4. **`--csv` only on the final step.** Intermediate steps emit JSON for chaining. Add `--csv` once, at the end.\n5. **`autocomplete` first** for: `naics_category`, `linkedin_category`, `company_tech_stack_tech`, `job_title`, `business_intent_topics`, `city_region`. Use returned standardized values, not raw user wording.\n6. **Never invent tool parameters.** Before the **first** `--args` execution of each distinct tool in a workflow, run `npx @vibeprospecting\u002Fvpai@latest \u003Ctool> --all-parameters` for that tool (once per tool per task unless you already printed its schema earlier in the same workflow). That command prints one JSON object to stdout: **`name`**, **`description`**, and **`inputSchema`** (the tool **input** JSON Schema). **Do this even when** the planned call matches the examples and you are not uncertain—examples can drift; the printed schema is authoritative. Run `--all-parameters` again if you change tools, filters, or shapes materially, or if anything still feels ambiguous. You may use examples and reference docs as shortcuts only **after** they align with that live schema. Build `--args` only from fields and shapes confirmed by **`inputSchema`** from `--all-parameters` (and examples when they match it).\n7. **`--session-id`** is a CLI flag (not inside `--args`). Use the **`session_id`** value returned by the MCP in each prior step's JSON. Omit only on the first call in a chain.\n8. **`fetch-entities-statistics` only when stats supports the full fetch.** Compare your planned **`fetch-entities`** payload to the **input schema** from **`fetch-entities-statistics --all-parameters`**. Call statistics **only if every** filter key, value shape, **`entity_type`**, and any scope you rely on (e.g. **`--session-id`** \u002F **`--businesses-table-name`**) is accepted by the statistics tool the same way it is for **`fetch-entities`**. If any part of the discovery query is missing from the stats schema, unsupported, or would require a different shape, **skip stats** — do not call it with a partial or guessed subset. When you do call it, reuse the **same** **`--args`** filter object (and supported flags) as **`fetch-entities`**, plus **`--tool-reasoning`**. Prefer running stats **before** presenting the sample so you can headline **5 of [total]** when the response includes a usable count. When you **did not** run statistics (or stats had no usable total), present **Sample preview (5 rows)** and tell the user Explorium has **much more** matching the same filters—**do not** quote how many remain, **do not** say statistics failed or a total was unavailable, and **never** invent a number. Call stats again before a full-scale fetch **if** filters or scope changed **and** the full fetch filter set still fits statistics.\n\n## Auth\n\n```bash\nmcp__cowork__request_cowork_directory path=~\u002F.config\u002Fvpai\nAPI_KEY=$(python3 -c \"import json;print(json.load(open('\u002Fsessions\u002F\u003Csession-id>\u002Fmnt\u002Fvpai\u002Fconfig.json'))['api_key'])\")\nnpx @vibeprospecting\u002Fvpai@latest config --api-key \"$API_KEY\"\n```\n\nIf the mount fails or `config.json` is missing, follow [`login.md`](references\u002Flogin.md).\n\n## Sample Gate\n\nThe sample is the **complete workflow on 5 entities**, not a fetch preview.\n\n**Universe vs sample:** The 5 rows are a **small fixed preview** so the user can validate filters and enrichment before spending quota. The underlying match set is typically **much larger** (often thousands or more). Do not equate \"we returned 5\" with \"only 5 exist.\" Ground volume with **`fetch-entities-statistics`** only when the **entire** planned **`fetch-entities`** filter set is valid for stats (rule 8); never guess a total.\n\n1. **When the full fetch filter set is supported by statistics**, run **`fetch-entities-statistics`** with the same discovery **`entity_type`**, **`filters`**, and supported CLI flags as the upcoming **`fetch-entities`** (per rule 8). Otherwise skip stats; still tell the user Explorium has **much more** for the same filters (no numeric total, no mention of statistics gaps).\n2. Fetch exactly 5 (`--number-of-results 5`).\n3. Run **every** subsequent step (`match-*`, `enrich-*`, `fetch-*-events`) on those 5.\n4. Show the **fully enriched final rows** as a markdown table with all useful columns.\n5. Stop. Wait for approval in a new message. Then run at full scale.\n\nNEVER stop after the fetch to ask for approval. Complete the full chain on 5 first.\n\nExample — user says \"find 100 Israeli companies, get 30 CEOs, find contact info\":\n- WRONG: fetch 5 companies → show table → ask \"continue?\"\n- RIGHT: when the **full** **`fetch-entities`** filter set is supported by **`fetch-entities-statistics`**, run stats first (same **`--args`** filters) → fetch 5 companies → fetch CEOs at those 5 → enrich CEOs with contacts → show final table (**5 of [total]** when stats gave a total; otherwise **Sample preview (5 rows)** plus a short line that **much more** matches exist for these filters—no count, no stats apology) → ask \"run full 100?\"\n\n### Presenting the sample\n\nAlways frame the table as a **sample**, not the full population.\n\n- **When statistics returned a usable total** (you only called stats because **every** **`fetch-entities`** filter was valid for **`fetch-entities-statistics`**): **Sample preview (5 of [total] matches)** — **[total]** must come from **`fetch-entities-statistics`**, never from counting the 5 rows.\n- **When you did not use a numeric total** (no stats, or no usable total): **Sample preview (5 rows)** and one plain sentence that Explorium has **much more** matching these filters—**do not** say how many more, **do not** mention statistics or missing totals, **never** invent **[total]**.\n\n`Results Found: [X] [entity type] from [Y] [companies\u002Fsources] [qualifier]` (optional context line)\n\n**Headline:** **Sample preview (5 of [total] matches):** only with a stats-backed **[total]**; otherwise **Sample preview (5 rows):** then a single framing line that **much more** records exist for the same filters (qualitative only).\n\nEnd with an explicit next step, for example: **After you confirm**, I will re-run the same tool(s) with full-scale limits (e.g. **`--number-of-results [user's N]`** where you used `fetch-entities`) to pull the real batch.\n\nWhen the preview is a subset of what the user asked for (more rows or fields available at scale), add:\n\n- With a stats-backed **[total]**: `More data available: Preview shows [n] of [total]. Confirm before I run the full export.`\n- Without a numeric **[total]**: say the preview is five rows, **much more** exists in Explorium for the same filters, and ask to confirm a full export—**do not** give a remaining count or mention why no total was shown.\n\nDo **not** mention export when everything the user asked for is already in chat.\n\n### Before the full export, confirm\n\n- Export size (cap on records).\n- Filter narrowing: industry, size, revenue, region, tech.\n- For prospects: title variants, dedupe by company.\n- For contacts: professional emails only or also personal\u002Fphones.\n\n## Workflow\n\n```\n0. Auth — see Auth section above (or login.md)\n1. npx @vibeprospecting\u002Fvpai@latest --help                    Discover tools\n2. Read references\u002F\u003Ctool>.md for workflow + caveats\n3. Before the first real `--args` for each tool: `npx @vibeprospecting\u002Fvpai@latest \u003Ctool> --all-parameters` (mandatory per tool, not only when uncertain). Prints the tool **input** schema as JSON. Run again if the planned call diverges from what you already validated.\n4. Build `--args` only from fields confirmed by that printed input schema (examples count only when they match it). If a parameter is not confirmed there, do not use it.\n5. When the **entire** planned **`fetch-entities`** filter set (and supported flags) matches **`fetch-entities-statistics`** input schema per **`--all-parameters`**: run **`fetch-entities-statistics`**, then sample (5 entities, full chain) — see Sample Gate\n6. npx @vibeprospecting\u002Fvpai@latest \u003Ctool> --args '\u003Cjson>' --tool-reasoning '\u003Cuser request>'\n7. Chain: --session-id \u003Csession_id> [--table-name \u003Ctable_name>] [--businesses-table-name \u003Cname> for prospect fetch from businesses]\n8. Final step only: add --csv\n```\n\nReference docs:\n\n- [`autocomplete.md`](references\u002Fautocomplete.md) — controlled-vocab lookups\n- [`fetch.md`](references\u002Ffetch.md) — `fetch-entities`, `fetch-*-events`\n- [`match.md`](references\u002Fmatch.md) — resolve known entities to IDs\n- [`enrich.md`](references\u002Fenrich.md) — enrichment after IDs\n- [`fetch-stats.md`](references\u002Ffetch-stats.md) — counts and market sizing\n- [`login.md`](references\u002Flogin.md) — auth fallback flow\n\n## Flags\n\n| Flag | Description |\n|------|-------------|\n| `--help` | List tools |\n| `--all-parameters` | Print `{ name, description, inputSchema }` to stdout (pretty-printed JSON). Run before the first `--args` for each tool in a workflow (and again if the tool or payload changes materially). Routine, not only when uncertain—the **`inputSchema`** field is authoritative. |\n| `--args '\u003Cjson>'` | Tool arguments |\n| `--session-id \u003Cid>` | Same workflow: pass **`session_id`** from the previous tool's JSON (opens the shared SQLite DB under `db_path`). |\n| `--table-name \u003Cname>` | **Required** with `--session-id` for **`enrich-business`**, **`enrich-prospects`**, **`fetch-businesses-events`**, and **`fetch-prospects-events`** (prior step's `table_name`). Optional for **`match-*`** only (disambiguate when multiple tables). |\n| `--businesses-table-name \u003Cname>` | For `fetch-entities` + `entity_type: prospects`: table whose rows supply `business_id` for the filter (with `--session-id`). |\n| `--number-of-results \u003Cn>` | For `fetch-entities`: total rows across pages (CLI paginates). Omit for one raw page. |\n| `--file-path \u003Cpath>` | For `match-business` \u002F `match-prospects`: path to a CSV file to match. Each row becomes one candidate. Requires `--schema`. |\n| `--schema '\u003Cjson>'` | Required with `--file-path`. JSON dict mapping CSV column headers to API field names. Business fields: `name`, `domain`. Prospect fields: `full_name`, `first_name`, `last_name`, `email`, `phone_number`, `linkedin`, `company_name`, `business_id`. |\n| `--csv` | Also write flattened CSV. **Final step only.** |\n\n## Filter Pattern\n\n```json\n{ \"values\": [\"v1\", \"v2\"], \"negate\": false }   \u002F\u002F include or exclude\n{ \"gte\": 6, \"lte\": 24 }                       \u002F\u002F range\ntrue | false | null                           \u002F\u002F boolean (not wrapped)\n```\n\n## Limits\n\n| Tool | Limit |\n|------|-------|\n| `match-business` | 50 per call |\n| `match-prospects` | 40 per call |\n| `enrich-business` | 50 IDs per call |\n| `enrich-prospects` | 50 IDs per call |\n| `fetch-businesses-events` \u002F `fetch-prospects-events` | Up to **20** IDs per MCP request (CLI chunks + merges). Pass **`event_types`** and **`timestamp_from`** in **`--args`**. Do not put **`business_ids`** \u002F **`prospect_ids`** in **`--args`** — IDs come only from **`--table-name`**. |\n| `fetch-entities` | use `--number-of-results`; CLI paginates. Don't pass `next_cursor` or `page_size` manually |\n\n## Common Workflows\n\nReplace `SESSION_ID` with the `session_id` from the previous step.\n\n### VP Engineering at SaaS in NY\n\n```bash\nnpx @vibeprospecting\u002Fvpai@latest autocomplete --args '{\"field\":\"linkedin_category\",\"query\":\"software\"}' --tool-reasoning 'find VP Eng at SaaS in NY'\n# When every fetch-entities filter (and flags) is valid for fetch-entities-statistics (--all-parameters):\nnpx @vibeprospecting\u002Fvpai@latest fetch-entities-statistics --args '{\"entity_type\":\"prospects\",\"filters\":{\"job_level\":{\"values\":[\"vice president\"]},\"job_department\":{\"values\":[\"engineering\"]},\"linkedin_category\":{\"values\":[\"Software Development\"]},\"company_region_country_code\":{\"values\":[\"US-NY\"]},\"has_email\":true}}' --tool-reasoning 'find VP Eng at SaaS in NY'\nnpx @vibeprospecting\u002Fvpai@latest fetch-entities --args '{\"entity_type\":\"prospects\",\"filters\":{\"job_level\":{\"values\":[\"vice president\"]},\"job_department\":{\"values\":[\"engineering\"]},\"linkedin_category\":{\"values\":[\"Software Development\"]},\"company_region_country_code\":{\"values\":[\"US-NY\"]},\"has_email\":true}}' --number-of-results 50 --tool-reasoning 'find VP Eng at SaaS in NY'\nnpx @vibeprospecting\u002Fvpai@latest enrich-prospects --args '{\"enrichments\":[\"contacts\",\"profiles\"]}' --session-id \u003Csession_id> --table-name \u003Cfetch_entities_table_from_prior_step> --csv --tool-reasoning 'find VP Eng at SaaS in NY'\n```\n\n### Companies that raised + use Salesforce\n\n```bash\nnpx @vibeprospecting\u002Fvpai@latest autocomplete --args '{\"field\":\"company_tech_stack_tech\",\"query\":\"salesforce\"}' --tool-reasoning 'companies that raised and use Salesforce'\n# When every fetch-entities filter (and flags) is valid for fetch-entities-statistics (--all-parameters):\nnpx @vibeprospecting\u002Fvpai@latest fetch-entities-statistics --args '{\"entity_type\":\"businesses\",\"filters\":{\"company_tech_stack_tech\":{\"values\":[\"Salesforce\"]},\"events\":{\"values\":[\"new_funding_round\"],\"last_occurrence\":60}}}' --tool-reasoning 'companies that raised and use Salesforce'\nnpx @vibeprospecting\u002Fvpai@latest fetch-entities --args '{\"entity_type\":\"businesses\",\"filters\":{\"company_tech_stack_tech\":{\"values\":[\"Salesforce\"]},\"events\":{\"values\":[\"new_funding_round\"],\"last_occurrence\":60}}}' --number-of-results 50 --tool-reasoning 'companies that raised and use Salesforce'\nnpx @vibeprospecting\u002Fvpai@latest fetch-businesses-events --args '{\"event_types\":[\"new_funding_round\"],\"timestamp_from\":\"2024-10-01\"}' --session-id \u003Csession_id> --table-name \u003Cfetch_entities_table_from_prior_step> --csv --tool-reasoning 'companies that raised and use Salesforce'\n```\n\n### Market sizing\n\n```bash\nnpx @vibeprospecting\u002Fvpai@latest fetch-entities-statistics --args '{\"entity_type\":\"businesses\",\"filters\":{\"linkedin_category\":{\"values\":[\"Hospital & Health Care\"]},\"company_country_code\":{\"values\":[\"US\"]}}}' --tool-reasoning 'market sizing US healthcare'\n```\n\n## Troubleshooting\n\n| Error | Solution |\n|-------|----------|\n| CLI install fails (`npx` unavailable, sandbox, permission denied) | Switch to the bundled Vibe Prospecting MCP connector and follow its tool descriptions; the rest of this file no longer applies. |\n| Auth \u002F 401 (connector \u002F Cowork) | Run Auth section above; if mount fails, follow [`login.md`](references\u002Flogin.md) |\n| Auth \u002F 401 (OpenClaw) | Run `npx @vibeprospecting\u002Fvpai@latest login` then `login --poll`. Or set `VP_API_KEY`. Restart gateway after. See Auth section above. |\n| `Not authenticated` (OpenClaw) | Neither `~\u002F.config\u002Fvpai\u002Fconfig.json` nor `VP_API_KEY` env var is present. Follow the OpenClaw Auth section. |\n| Plugin not showing tools in OpenClaw | Run `openclaw plugins list` — confirm `vpai` is listed. Re-install if needed: `openclaw plugins install .\u002Fvpai-plugin`. |\n| Tools missing after OpenClaw install | Gateway must restart: `openclaw gateway restart`. |\n| Missing **`session_id`** in JSON \u002F CLI refuses to chain | The MCP must return **`session_id`**; ensure you target production **`https:\u002F\u002Fvibeprospecting.explorium.ai\u002Fmcp`** (embedded in the npm CLI). Pass **`--session-id`** with that exact string on the next step. |\n| Wrong rows used when chaining | Pass **`--table-name`** matching the prior step's **`table_name`**. |\n| **`enrich-*` or `fetch-*-events` with `--session-id` but no `--table-name`** | **`--table-name`** is required for **`enrich-business`**, **`enrich-prospects`**, **`fetch-businesses-events`**, and **`fetch-prospects-events`** whenever you pass **`--session-id`**. |\n| Empty results | Check filter values; run `autocomplete` for controlled-vocab fields; re-check the relevant live **input** schema with `\u003Ctool> --all-parameters` |\n| `linkedin_category` + `naics_category` together | Mutually exclusive — use one |\n| JSON parse error | Validate JSON; check shell quoting |\n| Timeout on `fetch-entities`, `enrich-*`, `fetch-*-events`, or `match-*` with `--file-path` | **Re-run the exact same command** with the same `--session-id`, `--table-name`, `--args`, and (for match) `--file-path` \u002F `--schema`. The CLI resumes from the last checkpoint — completed ID batches are skipped, no work is repeated. If the job already completed on a prior run, the stored manifest is returned instantly with no API calls. |\n| Timeout without `--session-id` | Add `--session-id \u003Cany-stable-id>` to enable checkpointing, then retry. Without a session ID the CLI cannot resume. |\n",{"data":37,"body":41},{"name":4,"description":6,"compatibility":38,"metadata":39},"Run with `npx @vibeprospecting\u002Fvpai@latest`. 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Without a session ID the CLI cannot resume.",{"type":45,"tag":3887,"props":3888,"children":3889},"style",{},[3890],{"type":51,"value":3891},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":3893,"total":4014},[3894,3913,3931,3950,3967,3983,4002],{"slug":3895,"name":3895,"fn":3896,"description":3897,"org":3898,"tags":3899,"stars":25,"repoUrl":26,"updatedAt":3912},"amazon-location-service","integrate Amazon Location Service APIs","Integrates Amazon Location Service APIs for AWS applications. Use this skill when users want to add maps (interactive MapLibre or static images); geocode addresses to coordinates or reverse geocode coordinates to addresses; calculate routes, travel times, or service areas; find places and businesses through text search, nearby search, or autocomplete suggestions; retrieve detailed place information including hours, contacts, and addresses; monitor geographical boundaries with geofences; or track device locations. Covers authentication, SDK integration, and all Amazon Location Service capabilities.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3900,3903,3906,3909],{"name":3901,"slug":3902,"type":15},"API Development","api-development",{"name":3904,"slug":3905,"type":15},"AWS","aws",{"name":3907,"slug":3908,"type":15},"Maps","maps",{"name":3910,"slug":3911,"type":15},"Navigation","navigation","2026-07-12T08:13:53.294026",{"slug":3914,"name":3914,"fn":3915,"description":3916,"org":3917,"tags":3918,"stars":25,"repoUrl":26,"updatedAt":3930},"amplify-workflow","build full-stack apps with AWS Amplify","Build and deploy full-stack web and mobile apps with AWS Amplify Gen2 (TypeScript code-first). Covers auth (Cognito), data (AppSync\u002FDynamoDB including schema modeling, enum types, relationships, authorization rules), storage (S3), functions, APIs, and AI (Amplify AI Kit with Bedrock). Supports React, Next.js, Vue, Angular, React Native, Flutter, Swift, and Android. Always use this skill for Amplify Gen2 topics — even for questions you think you know — it contains validated, version-specific patterns that prevent common mistakes. TRIGGER when: user mentions Amplify Gen2; project has amplify\u002F directory or amplify_outputs; code imports @aws-amplify packages; user asks about defineBackend, defineAuth, defineData, defineStorage, or npx ampx. SKIP: Amplify Gen1 (amplify CLI v6), standalone SAM\u002FCDK without Amplify (use aws-serverless), direct Bedrock without Amplify AI Kit (use bedrock).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3919,3920,3921,3924,3927],{"name":969,"slug":966,"type":15},{"name":3904,"slug":3905,"type":15},{"name":3922,"slug":3923,"type":15},"Database","database",{"name":3925,"slug":3926,"type":15},"Frontend","frontend",{"name":3928,"slug":3929,"type":15},"TypeScript","typescript","2026-07-12T08:13:47.134012",{"slug":3932,"name":3932,"fn":3933,"description":3934,"org":3935,"tags":3936,"stars":25,"repoUrl":26,"updatedAt":3949},"analyzer","analyze queried data for trends","Analyze queried data for trends, week-over-week comparisons, distributions, funnels, cohorts, top-N lists, anomalies, sanity checks, and report-ready findings. Use after or alongside ClickHouse queries when the user wants insight rather than raw rows.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3937,3940,3943,3946],{"name":3938,"slug":3939,"type":15},"Analytics","analytics",{"name":3941,"slug":3942,"type":15},"ClickHouse","clickhouse",{"name":3944,"slug":3945,"type":15},"Data Analysis","data-analysis",{"name":3947,"slug":3948,"type":15},"Statistics","statistics","2026-07-12T08:14:05.606036",{"slug":3951,"name":3951,"fn":3952,"description":3953,"org":3954,"tags":3955,"stars":25,"repoUrl":26,"updatedAt":3966},"artifact-management","manage and organize analysis artifacts","Save, organize, and describe reusable analysis artifacts such as SQL, result snapshots, CSV exports, summaries, caveats, plots, and report-ready files. Use when users ask to save, export, share, cite, reproduce, or organize data-analysis outputs.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3956,3957,3960,3963],{"name":3944,"slug":3945,"type":15},{"name":3958,"slug":3959,"type":15},"Productivity","productivity",{"name":3961,"slug":3962,"type":15},"Reporting","reporting",{"name":3964,"slug":3965,"type":15},"SQL","sql","2026-07-12T08:14:09.265555",{"slug":3968,"name":3968,"fn":3969,"description":3970,"org":3971,"tags":3972,"stars":25,"repoUrl":26,"updatedAt":3982},"attorney-assist","connect with attorneys for legal consultation","Connects the user with a LegalZoom attorney for legal consultation. Use when a user asks about attorneys, lawyers, or legal help, or when contract review reveals high risks or low-confidence findings.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3973,3976,3979],{"name":3974,"slug":3975,"type":15},"Contracts","contracts",{"name":3977,"slug":3978,"type":15},"Legal","legal",{"name":3980,"slug":3981,"type":15},"Risk Assessment","risk-assessment","2026-07-12T08:13:45.878361",{"slug":3984,"name":3984,"fn":3985,"description":3986,"org":3987,"tags":3988,"stars":25,"repoUrl":26,"updatedAt":4001},"building-pydantic-ai-agents","build AI agents with Pydantic AI","Build AI agents with Pydantic AI — tools, capabilities (including on-demand loading), structured output, streaming, testing, and multi-agent patterns. Use when the user mentions Pydantic AI, imports pydantic_ai, or asks to build an AI agent, add tools\u002Fcapabilities, defer capability loading, stream output, define agents from YAML, or test agent behavior.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3989,3992,3995,3998],{"name":3990,"slug":3991,"type":15},"Agents","agents",{"name":3993,"slug":3994,"type":15},"LLM","llm",{"name":3996,"slug":3997,"type":15},"Multi-Agent","multi-agent",{"name":3999,"slug":4000,"type":15},"Python","python","2026-07-12T08:14:01.893781",{"slug":3942,"name":3942,"fn":4003,"description":4004,"org":4005,"tags":4006,"stars":25,"repoUrl":26,"updatedAt":4013},"query ClickHouse databases via CLI","Connect to and query ClickHouse (a local server or a ClickHouse Cloud service) from the terminal using the official clickhousectl CLI, including the browser OAuth login flow. Use when the user wants to run SQL against ClickHouse, explore schemas and tables, inspect Cloud services, or authenticate clickhousectl. For building a local dev environment or deploying to Cloud, defer to the official ClickHouse skills (see Scope).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4007,4008,4011,4012],{"name":3938,"slug":3939,"type":15},{"name":4009,"slug":4010,"type":15},"CLI","cli",{"name":3941,"slug":3942,"type":15},{"name":3922,"slug":3923,"type":15},"2026-07-12T08:14:06.829692",43,{"items":4016,"total":4142},[4017,4024,4032,4039,4046,4052,4059,4066,4078,4096,4116,4129],{"slug":3895,"name":3895,"fn":3896,"description":3897,"org":4018,"tags":4019,"stars":25,"repoUrl":26,"updatedAt":3912},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4020,4021,4022,4023],{"name":3901,"slug":3902,"type":15},{"name":3904,"slug":3905,"type":15},{"name":3907,"slug":3908,"type":15},{"name":3910,"slug":3911,"type":15},{"slug":3914,"name":3914,"fn":3915,"description":3916,"org":4025,"tags":4026,"stars":25,"repoUrl":26,"updatedAt":3930},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4027,4028,4029,4030,4031],{"name":969,"slug":966,"type":15},{"name":3904,"slug":3905,"type":15},{"name":3922,"slug":3923,"type":15},{"name":3925,"slug":3926,"type":15},{"name":3928,"slug":3929,"type":15},{"slug":3932,"name":3932,"fn":3933,"description":3934,"org":4033,"tags":4034,"stars":25,"repoUrl":26,"updatedAt":3949},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4035,4036,4037,4038],{"name":3938,"slug":3939,"type":15},{"name":3941,"slug":3942,"type":15},{"name":3944,"slug":3945,"type":15},{"name":3947,"slug":3948,"type":15},{"slug":3951,"name":3951,"fn":3952,"description":3953,"org":4040,"tags":4041,"stars":25,"repoUrl":26,"updatedAt":3966},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4042,4043,4044,4045],{"name":3944,"slug":3945,"type":15},{"name":3958,"slug":3959,"type":15},{"name":3961,"slug":3962,"type":15},{"name":3964,"slug":3965,"type":15},{"slug":3968,"name":3968,"fn":3969,"description":3970,"org":4047,"tags":4048,"stars":25,"repoUrl":26,"updatedAt":3982},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4049,4050,4051],{"name":3974,"slug":3975,"type":15},{"name":3977,"slug":3978,"type":15},{"name":3980,"slug":3981,"type":15},{"slug":3984,"name":3984,"fn":3985,"description":3986,"org":4053,"tags":4054,"stars":25,"repoUrl":26,"updatedAt":4001},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4055,4056,4057,4058],{"name":3990,"slug":3991,"type":15},{"name":3993,"slug":3994,"type":15},{"name":3996,"slug":3997,"type":15},{"name":3999,"slug":4000,"type":15},{"slug":3942,"name":3942,"fn":4003,"description":4004,"org":4060,"tags":4061,"stars":25,"repoUrl":26,"updatedAt":4013},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4062,4063,4064,4065],{"name":3938,"slug":3939,"type":15},{"name":4009,"slug":4010,"type":15},{"name":3941,"slug":3942,"type":15},{"name":3922,"slug":3923,"type":15},{"slug":4067,"name":4067,"fn":4068,"description":4069,"org":4070,"tags":4071,"stars":25,"repoUrl":26,"updatedAt":4077},"cline-session-history","search and browse Cline session history","Search and browse Cline session history. Use when the user asks to find, list, inspect, or export Cline sessions by time period, prompt content, status, model, provider, source, mode, workspace, or other criteria. Also use when the user wants to read a session transcript or export sessions to a directory. Trigger phrases include \"find my session\", \"search my session history\", \"show me past sessions\", \"what was that session where\", \"find the session that started with\", and any mention of past Cline conversations.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4072,4073,4076],{"name":3990,"slug":3991,"type":15},{"name":4074,"slug":4075,"type":15},"History","history",{"name":3958,"slug":3959,"type":15},"2026-07-19T06:03:13.945151",{"slug":4079,"name":4079,"fn":4080,"description":4081,"org":4082,"tags":4083,"stars":25,"repoUrl":26,"updatedAt":4095},"convex-design","build reactive backends with Convex","Design and build reactive, type-safe, production-grade backends on Convex. Covers schema, queries\u002Fmutations\u002Factions, indexes, auth, file storage, scheduling, real-time multiplayer, mobile backends, and LLM\u002Fagent workflows on Convex's one-platform stack.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4084,4085,4088,4089,4092],{"name":969,"slug":966,"type":15},{"name":4086,"slug":4087,"type":15},"Backend","backend",{"name":3922,"slug":3923,"type":15},{"name":4090,"slug":4091,"type":15},"Real-time","real-time",{"name":4093,"slug":4094,"type":15},"Storage","storage","2026-07-12T08:13:37.101253",{"slug":4097,"name":4097,"fn":4098,"description":4099,"org":4100,"tags":4101,"stars":25,"repoUrl":26,"updatedAt":4115},"cosmosdb-best-practices","optimize Azure Cosmos DB performance","Azure Cosmos DB performance optimization and best practices guidelines for NoSQL,\npartitioning, queries, SDK usage, and vector search. Use when writing, reviewing,\nor refactoring code that interacts with Azure Cosmos DB, designing data models,\noptimizing queries, or implementing high-performance database operations.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4102,4105,4108,4109,4112],{"name":4103,"slug":4104,"type":15},"Azure","azure",{"name":4106,"slug":4107,"type":15},"Cosmos DB","cosmos-db",{"name":3922,"slug":3923,"type":15},{"name":4110,"slug":4111,"type":15},"NoSQL","nosql",{"name":4113,"slug":4114,"type":15},"Performance","performance","2026-07-12T08:13:54.531719",{"slug":4117,"name":4117,"fn":4118,"description":4119,"org":4120,"tags":4121,"stars":25,"repoUrl":26,"updatedAt":4128},"data-analyst","analyze ClickHouse analytics data","Act as an interactive data analyst for ClickHouse-backed analytics. Use when the user asks questions about internal data, metrics, dashboards, telemetry, active users, revenue, funnels, trends, distributions, or wants an analyst-style conversation, ad hoc SQL, charts, or a data export against ClickHouse (local or ClickHouse Cloud).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4122,4123,4124,4127],{"name":3938,"slug":3939,"type":15},{"name":3941,"slug":3942,"type":15},{"name":4125,"slug":4126,"type":15},"Dashboards","dashboards",{"name":3944,"slug":3945,"type":15},"2026-07-12T08:13:31.975246",{"slug":4130,"name":4130,"fn":4131,"description":4132,"org":4133,"tags":4134,"stars":25,"repoUrl":26,"updatedAt":4141},"dataproc-skills","manage Dataproc clusters and jobs","Skills to interact with your Dataproc clusters and jobs.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4135,4138],{"name":4136,"slug":4137,"type":15},"Data Engineering","data-engineering",{"name":4139,"slug":4140,"type":15},"Operations","operations","2026-07-12T08:13:42.179275",45]