# Enriching Tables > Enrich any CSV of companies or people with web-sourced data (employee count, revenue, funding, tech stack, work emails, LinkedIn, and custom fields) using the @brightdata/enrich CLI. Use this skill whenever the user wants to enrich, augment, fill in, or research rows of a spreadsheet or CSV — leads, prospects, accounts, contacts, a CRM export, or any table of companies/domains/emails — or mentions Bright Data enrichment, the `enrich` command, lead enrichment, data enrichment, or "add a column with X" to a list. Covers first-time onboarding (Bright Data + OpenRouter setup), running enrichments, and publishing this skill on skills.sh. - Skill: `brightdata/enriching-tables` (Agent Skill, multi-file: 5 files) - Install (CLI): `npx skillmds@latest add brightdata/enriching-tables` - Raw SKILL.md: https://api.skillmd.com/api/skills/brightdata/enriching-tables/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Data & Analytics - Author: brightdata (https://skillmd.com/u/brightdata) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/brightdata/enriching-tables --- # Enriching Tables with @brightdata/enrich `@brightdata/enrich` (CLI command: `enrich`) turns a flat CSV into an enriched one. Each row is researched on the live web through Bright Data's infrastructure and an LLM agent swarm, and new columns are appended — company size, funding, tech stack, work emails, LinkedIn URLs, or anything you can describe in plain English. Every run is resumable, streams progress, and reports cost. This skill takes a user from zero (no account) to a finished enriched CSV, and assumes nothing about prior Bright Data experience. ## When you reach for this Any time a user has a table and wants more columns sourced from the web: a list of company domains that needs employee counts and funding stages, a Salesforce export missing industries, a contact list that needs verified work emails, or a vague "can you find X for each of these." If they hand you a CSV and describe data they don't yet have, this is the tool. ## The shape of the work The flow is always the same four beats. Do them in order; don't skip the dry run. ``` Enrichment Progress: - [ ] 1. Confirm prerequisites (Node ≥20, four credentials resolve) - [ ] 2. Inspect the input CSV (identifier column, what's already filled) - [ ] 3. Dry-run to lock config + estimate cost, then get the user's OK - [ ] 4. Run the real enrichment, report output path + cost ``` Copy that checklist into your working notes and tick items off — it keeps you from spending the user's money before they've approved the plan. ## Step 1 — Prerequisites The CLI needs **Node.js ≥ 20** and **four credentials**. If the user has never set this up, walk them through `references/onboarding.md` — it covers creating a Bright Data account, provisioning the two required zones, and getting an LLM key, with where-to-click pointers. Don't paraphrase those steps from memory; read that file and follow it. The four credentials: | Variable | What it is | Where it comes from | |---|---|---| | `BRIGHT_DATA_API_KEY` | Bright Data account API token | Bright Data dashboard → Settings → API keys | | `BRIGHT_DATA_SERP_ZONE` | name of a **SERP API** zone | Bright Data dashboard → Proxies & Scraping → your SERP zone | | `BRIGHT_DATA_UNLOCKER_ZONE` | name of a **Web Unlocker** zone | Bright Data dashboard → Proxies & Scraping → your Unlocker zone | | `OPENROUTER_API_KEY` | LLM provider key | openrouter.ai/keys (or use `OPENAI_API_KEY` / `ANTHROPIC_API_KEY` instead) | There are two ways to supply them. **Environment variables** (or a `.env` file in the working directory) always take precedence, which is what you want for scripted/non-interactive runs: ```bash export BRIGHT_DATA_API_KEY=... export BRIGHT_DATA_SERP_ZONE=... export BRIGHT_DATA_UNLOCKER_ZONE=... export OPENROUTER_API_KEY=... ``` Or the user can store them once with the interactive setup (saved to a `0600` config file in their OS config dir): ```bash npx @brightdata/enrich login ``` `login` validates each credential against the live API before saving — a wrong key fails fast here rather than mid-run. To wipe stored credentials, `enrich logout`. **Verify before doing anything else.** Run the bundled preflight, which checks the Node version and confirms all four credentials resolve (via a dry run, so it spends nothing): ```bash bash scripts/preflight.sh path/to/input.csv ``` If it reports a missing credential, send the user to `references/onboarding.md` for the one that's missing rather than guessing. ## Step 2 — Inspect the CSV Look at the file before configuring the run. You need to know two things: - **The identifier column** — the column the agents use to find each entity on the web. A company **domain** or **website** is ideal; a company **name** works; for people, an **email** plus first/last name columns. The CLI auto-detects this, but eyeball it so you can override with `--column` if the guess would be wrong (e.g. a file with both `domain` and `personal_domain`). - **What's already filled** — there's no point (and no spend) re-fetching columns the file already has. Enrich the gaps. A quick `head` of the file is enough. For the example file in this repo: ```bash head -5 examples/companies.csv # company,domain,hq_country # Stripe,stripe.com,United States # ... ``` Here `domain` is the natural identifier. ## Step 3 — Dry run, then get approval **Never kick off a paid run without a dry run first.** `--dry-run` resolves the full config — identifier column, the exact fields it will add, output path, and a cost estimate — and exits without touching any API. ```bash npx @brightdata/enrich examples/companies.csv \ --describe "employee count, total funding raised, primary tech stack" \ --dry-run ``` You'll get back something like the columns it will add, the detected identifier, and `Estimated: ~$X.XX (Bright Data) + ~$Y.YY (LLM)`. **Show the user this estimate and the field list, and wait for an explicit go-ahead** before the real run — especially for files over a few dozen rows. Cost scales with rows × fields; a 5,000-row file is real money. Decide **how to specify fields** (see the full catalog in `references/fields.md`): - `--describe ""` — natural language. The CLI first tries to map your words onto preset fields; if it can't, an LLM designs custom fields from the description. Use this for anything bespoke ("their Series B lead investor", "whether they use Kubernetes"). - `--fields a,b,c` — exact preset field names, comma-separated. Faster and deterministic. Use when you know the names. `--describe` and `--fields` are mutually exclusive. ## Step 4 — Run it Once approved, drop `--dry-run`: ```bash npx @brightdata/enrich examples/companies.csv \ --describe "employee count, total funding raised, primary tech stack" ``` The enriched file is written to `.enriched.csv` by default (override with `-o`). Progress streams to stderr with a live cost meter and ETA; the final summary prints rows done/skipped/errored, total cost split by LLM vs Bright Data, and the output path. **Report that summary and the output path back to the user.** ### The options that matter most | Option | Use it when | Default | |---|---|---| | `--describe ""` | You want fields in plain English (incl. custom) | — | | `--fields a,b,c` | You know the exact preset names | — | | `--column ` | Auto-detection picks the wrong identifier | auto | | `--first-name ` / `--last-name ` | Enriching **people** — lets agents disambiguate same-company contacts | — | | `-o, --output ` | You want a specific output filename | `.enriched.csv` | | `--concurrency ` | Tune rows-in-flight (lower if rate-limited, higher to go faster) | 30 | | `--dry-run` | Always, before a real run | off | | `--json` | You need machine-readable NDJSON instead of a CSV (pipe to `jq`) | off | | `--no-resume` | You want to overwrite rather than continue a prior run | resume on | | `-q` / `-v` | Quiet (summary only) / verbose (every agent step) | normal | ### Resuming is automatic If a run is interrupted (Ctrl-C, crash, or you just stop it), **re-run the exact same command** and it picks up where it left off — it checks the existing output's header and skips rows already written. This only works if the field set matches, so keep `--describe`/`--fields` identical. To start fresh instead, pass `--no-resume` or delete the output file. This makes large files safe to run in chunks. ### Enriching people, not just companies For contact-level data (work email, LinkedIn, title, seniority), point the CLI at the name columns so it can tell two people at the same company apart: ```bash npx @brightdata/enrich contacts.csv \ --first-name first_name --last-name last_name --column work_email \ --fields person_email,person_linkedin_url,person_title,person_seniority ``` ## Cost — set expectations honestly Bright Data bills roughly **$0.0015 per tool call**; a typical row touches 5–15 calls depending on how much you ask for. LLM cost is separate and paid to your provider. As a rule of thumb a 5-field CRM fill is well under a cent of Bright Data spend per row; deep person+company enrichment runs a few cents. The `--dry-run` estimate is your source of truth — always surface it. Compared to commercial enrichment vendors at $0.50–$2.00/row, this is one to two orders of magnitude cheaper, but it is **not free**, so confirm before large runs. ## When something goes wrong For credential errors, header-mismatch on resume, empty-field results, rate limits, and other failure modes, see `references/troubleshooting.md` — match the error message to its row and follow the fix. Don't retry a failing command unchanged; diagnose first. ## Field catalog The 36 built-in preset fields and 6 quick-start bundles (Startup Prospecting, Enterprise Research, Quick CRM Fill, Competitor Analysis, Person Lookup, Full Company + Person) are listed with descriptions in `references/fields.md`. Read it when the user wants specific named fields or you need to translate a request into the right `--fields` list. ## Installing / publishing this skill This skill lives at `skills/enriching-tables/SKILL.md` in the `brightdata/open-enrich` repo — the layout skills.sh indexes automatically — so users install it with `npx skills add brightdata/open-enrich/skills/enriching-tables`. Listing details and the README badge are documented in the repo's main README ("Or drive it from your coding agent"); publishing is a one-time author task, not part of running an enrichment.