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parallel-data-enrichment

Bulk data enrichment. Adds web-sourced fields (CEO names, funding, contact info) to lists of companies, people, or products. Use for enriching CSV files or inline data. Supports multi-turn: pass --previous-interaction-id from a prior research task to carry context forward.

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价格未确认★ 77 GitHub Stars目录更新于 · 2026年9月26日agent-skill

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Data Enrichment

Enrich: $ARGUMENTS

Before starting

Inform the user that enrichment may take several minutes depending on the number of rows and fields requested.

Optional: Suggest output columns

If the user gave a vague intent ("enrich these companies with useful info") and you're not sure what columns to add, ask the API for a suggestion before kicking off the run:

parallel-cli enrich suggest "Find CEO and recent funding info" --json

The response is an envelope: {title, processor, enriched_columns, warnings}. Extract just the enriched_columns array (not the whole envelope) and pass it as the value of --enriched-columns on enrich run, in place of --intent. These flags are alternative ways to specify what to enrich. If suggest returned a processor, pass it explicitly via --processor on the run call. Skip this section if the user already specified the fields they want.

enrich suggest requires parallel-cli ≥ 0.3.0. If only that command is missing, skip the optional suggestion step and use --intent in step 1. Suggest an installation-specific upgrade from Setup. Do not classify authentication, API or invalid-input failures as an older CLI. An intent-based run itself requests a suggestion; explicit columns default to core-fast, while intent can select another processor unless --processor overrides it.

Step 1: Start the enrichment

Use ONE of these command patterns (substitute user's actual data):

For inline data:

parallel-cli enrich run --data '[{"company": "Google"}, {"company": "Microsoft"}]' --intent "CEO name and founding year" --target "output.csv" --no-wait --json

For CSV file:

parallel-cli enrich run --source-type csv --source "input.csv" --target "output.csv" --source-columns '[{"name": "company", "description": "Company name"}]' --intent "CEO name and founding year" --no-wait --json

If this is a follow-up to a previous research task and you have its interaction_id, add context chaining:

parallel-cli enrich run --data '...' --intent "..." --target "output.csv" --no-wait --json --previous-interaction-id "$INTERACTION_ID"

This reuses the prior Task's context. Context chaining is unavailable for Zero Data Retention (ZDR) accounts, so omit the flag there and include the needed context explicitly. Enrichment does not return a new interaction_id; retain the prior Task ID for later follow-ups. A taskgroup_id or Search/Extract session_id is not a Task interaction ID.

IMPORTANT: Always include --no-wait so the command returns immediately instead of blocking.

Save the --json output's taskgroup_id, url and num_runs immediately. There is no interaction_id field. If creation is interrupted or its response is lost, inspect whether the group was created before submitting another run. Immediately tell the user:

Enrichment has been kicked off
The monitoring URL where they can track progress

The group runs server-side; polling can resume later using its saved ID.

Step 2: Poll for results

Pick a persistent, run-specific output path (e.g., enrichment-acme-tgrp-<id>.json). Polling overwrites its output file, so inspect any existing file and use a new path unless replacement is intended. The output is JSON regardless of extension: an array of rows with input and either output or error. Async polling does not include basis or per-row interaction IDs; do not invent citations or context IDs.

parallel-cli enrich poll "$TASKGROUP_ID" --timeout 60 --output "enrichment-<descriptive-name>-<group-id>.json"

Important:

Keep polls bounded; --timeout 60 allows progress updates between waits.
The --target from step 1 is unused in --no-wait mode. Only --output here determines where results are saved, and the file is always JSON.
A completed group can include failed rows. Count rows containing output separately from rows containing error and compare their total with num_runs; an empty or incomplete file is not successful enrichment of the entire input.

If polling times out or is interrupted

Timeout exit 5 or interruption ends the local wait. Check group state before saying it is still running:

parallel-cli enrich status "$TASKGROUP_ID" --json

Inspect is_active, status_counts and num_runs. Resume the same poll for an active group, or retrieve results for an inactive group and report failures or unresolved rows. Do not recreate the group on a timeout or automatically rerun failed rows. A local file-write failure can be retried with the same group ID and a writable output path.

If the user requested CSV

Convert the saved JSON locally into a separate CSV. Preserve every original input column and row, including duplicate and failed rows; keep enrichment fields separate from conflicting input names and include an error column for failures. Do not assume streamed rows match original input order or guess a join when row identity is ambiguous. Validate the row count and leave the input CSV untouched. This is local conversion, not a CSV produced by async polling; report both JSON and CSV paths.

Response format

After step 1: Share the monitoring URL (for tracking progress).

After step 2:

Report successful, failed and total row counts, with any missing results called out.
Preview a few successful rows and a representative failure if present, without claiming all rows succeeded.
Tell the user the full path to the output file

After completion, link the saved output rather than repeating the monitoring URL.

Setup

If parallel-cli is not found, install and authenticate:

/parallel:parallel-cli-setup

If a documented option or command is missing, identify the install method and upgrade through that method: standalone parallel-cli update; pipx pipx upgrade parallel-web-tools; uv uv tool upgrade parallel-web-tools; Homebrew brew upgrade parallel-web/tap/parallel-cli; npm npm update -g parallel-web-cli. Recheck version and help in the agent's terminal before retrying.

For authentication or API errors, inspect the returned message. A 403 can indicate permissions, account policy or billing; it does not prove low balance. Check parallel-cli auth --json and its authenticated boolean when relevant without exposing credentials. Only a billing-specific error warrants a balance check, and adding funds needs explicit confirmation. Reuse saved group IDs; do not automatically retry an ambiguous creation.

查看来源 ↗

文件元数据

name: parallel-data-enrichment
description: "Bulk data enrichment. Adds web-sourced fields (CEO names, funding, contact info) to lists of companies, people, or products. Use for enriching CSV files or inline data. Supports multi-turn: pass --previous-interaction-id from a prior research task to carry context forward."
user-invocable: true
argument-hint: <file or entities> with <fields to add>
compatibility: Requires parallel-cli and internet access.
allowed-tools: Bash(parallel-cli:*)
metadata:
  author: parallel

查看原始文本

---
name: parallel-data-enrichment
description: "Bulk data enrichment. Adds web-sourced fields (CEO names, funding, contact info) to lists of companies, people, or products. Use for enriching CSV files or inline data. Supports multi-turn: pass --previous-interaction-id from a prior research task to carry context forward."
user-invocable: true
argument-hint: <file or entities> with <fields to add>
compatibility: Requires parallel-cli and internet access.
allowed-tools: Bash(parallel-cli:*)
metadata:
author: parallel
---

# Data Enrichment

Enrich: $ARGUMENTS

## Before starting

Inform the user that enrichment may take several minutes depending on the number of rows and fields requested.

## Optional: Suggest output columns

If the user gave a vague intent ("enrich these companies with useful info") and you're not sure what columns to add, ask the API for a suggestion before kicking off the run:

```bash
parallel-cli enrich suggest "Find CEO and recent funding info" --json
```

The response is an envelope: `{title, processor, enriched_columns, warnings}`. Extract just the **`enriched_columns` array** (not the whole envelope) and pass it as the value of `--enriched-columns` on `enrich run`, **in place of `--intent`**. These flags are alternative ways to specify what to enrich. If `suggest` returned a `processor`, pass it explicitly via `--processor` on the `run` call. Skip this section if the user already specified the fields they want.

> `enrich suggest` requires `parallel-cli` ≥ 0.3.0. If only that command is missing, skip the optional suggestion step and use `--intent` in step 1. Suggest an installation-specific upgrade from Setup. Do not classify authentication, API or invalid-input failures as an older CLI. An intent-based run itself requests a suggestion; explicit columns default to `core-fast`, while intent can select another processor unless `--processor` overrides it.

## Step 1: Start the enrichment

Use ONE of these command patterns (substitute user's actual data):

For inline data:

```bash
parallel-cli enrich run --data '[{"company": "Google"}, {"company": "Microsoft"}]' --intent "CEO name and founding year" --target "output.csv" --no-wait --json
```

For CSV file:

```bash
parallel-cli enrich run --source-type csv --source "input.csv" --target "output.csv" --source-columns '[{"name": "company", "description": "Company name"}]' --intent "CEO name and founding year" --no-wait --json
```

If this is a **follow-up** to a previous research task and you have its `interaction_id`, add context chaining:

```bash
parallel-cli enrich run --data '...' --intent "..." --target "output.csv" --no-wait --json --previous-interaction-id "$INTERACTION_ID"
```

This reuses the prior Task's context. Context chaining is unavailable for Zero Data Retention (ZDR) accounts, so omit the flag there and include the needed context explicitly. Enrichment does **not** return a new `interaction_id`; retain the prior Task ID for later follow-ups. A `taskgroup_id` or Search/Extract `session_id` is not a Task interaction ID.

**IMPORTANT:** Always include `--no-wait` so the command returns immediately instead of blocking.

Save the `--json` output's `taskgroup_id`, `url` and `num_runs` immediately. There is no `interaction_id` field. If creation is interrupted or its response is lost, inspect whether the group was created before submitting another run. Immediately tell the user:

- Enrichment has been kicked off
- The monitoring URL where they can track progress

The group runs server-side; polling can resume later using its saved ID.

## Step 2: Poll for results

Pick a persistent, run-specific output path (e.g., `enrichment-acme-tgrp-<id>.json`). Polling overwrites its output file, so inspect any existing file and use a new path unless replacement is intended. The output is JSON regardless of extension: an array of rows with `input` and either `output` or `error`. Async polling does not include basis or per-row interaction IDs; do not invent citations or context IDs.

```bash
parallel-cli enrich poll "$TASKGROUP_ID" --timeout 60 --output "enrichment-<descriptive-name>-<group-id>.json"
```

Important:

- Keep polls bounded; `--timeout 60` allows progress updates between waits.
- The `--target` from step 1 is unused in `--no-wait` mode. Only `--output` here determines where results are saved, and the file is always JSON.
- A completed group can include failed rows. Count rows containing `output` separately from rows containing `error` and compare their total with `num_runs`; an empty or incomplete file is not successful enrichment of the entire input.

### If polling times out or is interrupted

Timeout exit 5 or interruption ends the local wait. Check group state before saying it is still running:

```bash
parallel-cli enrich status "$TASKGROUP_ID" --json
```

Inspect `is_active`, `status_counts` and `num_runs`. Resume the same poll for an active group, or retrieve results for an inactive group and report failures or unresolved rows. Do not recreate the group on a timeout or automatically rerun failed rows. A local file-write failure can be retried with the same group ID and a writable output path.

### If the user requested CSV

## Response format

**After step 1:** Share the monitoring URL (for tracking progress).

**After step 2:**

1. Report successful, failed and total row counts, with any missing results called out.
2. Preview a few successful rows and a representative failure if present, without claiming all rows succeeded.
3. Tell the user the full path to the output file

After completion, link the saved output rather than repeating the monitoring URL.

## Setup

If `parallel-cli` is not found, install and authenticate:

```bash
/parallel:parallel-cli-setup
```

If a documented option or command is missing, identify the install method and upgrade through that method: standalone `parallel-cli update`; pipx `pipx upgrade parallel-web-tools`; uv `uv tool upgrade parallel-web-tools`; Homebrew `brew upgrade parallel-web/tap/parallel-cli`; npm `npm update -g parallel-web-cli`. Recheck version and help in the agent's terminal before retrying.

For authentication or API errors, inspect the returned message. A `403` can indicate permissions, account policy or billing; it does not prove low balance. Check `parallel-cli auth --json` and its `authenticated` boolean when relevant without exposing credentials. Only a billing-specific error warrants a balance check, and adding funds needs explicit confirmation. Reuse saved group IDs; do not automatically retry an ambiguous creation.

查看并核实来源

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许可证: MIT
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已记录技能来源

已记录技能指令路径，不代表本站运行测试、安全保证或兼容性认证。

安装前审查: 避免自动安装

许可证: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
缺少 AI 审查批准
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 77 GitHub stars
Stars/forks activity: 77 stars, 10 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

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工具列表来自元数据，并非已测试的兼容性；Agent 提示词是建议的交接方式。

从一个小任务开始

1阅读来源，确认输入、预期输出、依赖和权限。
2先让 Agent 提出计划，批准环境配置和费用，再进行隔离的小规模测试。
3检查输出和变更文件，只报告实际执行结果，并保留来源版本以便复现。

请在来源中核实依赖、API 密钥及第三方费用。公开仓库不代表所有服务免费。

来源与使用须知

已收录静态检查通过

仓库元数据和审核信号仅供参考。受欢迎、已发现来源、成功运行是不同的事实。

来源仓库: parallel-web/parallel-agent-skills
许可证: MIT
版本: Unknown
最近 GitHub 推送: 2026年9月25日
目录更新于: 2026年9月26日
技能指令路径: skills/parallel-data-enrichment/SKILL.md @ 8fc1fc426e79

版本来自目录元数据，使用前请核实来源发布记录。

质量

60/100

有潜力

信任

61/100

仅限沙盒

审计

74/100

需审查

打开完整审计查看评估报告

Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
缺少 AI 审查批准
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 77 GitHub stars
Stars/forks activity: 77 stars, 10 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Verified installs: —
结果: —

复制不等于安装。安装数需有成功安装回报，不代表全面的质量保证。

Agent 接入

本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号，让 Agent 无需抓取界面即可排序。

打开安装 API LLM 文本格式打开 Manifest 自动解析计划

更多详情

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      "GitHub adoption: 77 GitHub stars",
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    ]
  },
  "audit": {
    "score": 74,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Financial research output is not financial advice; require human review before any live investment decision",
      "AI review approval is missing",
      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 77 GitHub stars"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 60,
    "label": "Promising"
  },
  "supply": {
    "track": "Research and knowledge work",
    "scenario": "Research agents",
    "maintenance": "18d since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "high-compliance environments without internal security review",
    "No major risk signals from current metadata",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Financial research output is not financial advice; require human review before any live investment decision",
    "AI review approval is missing"
  ],
  "agent_contract": {
    "task_input": "Use parallel-data-enrichment in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 69/100 Manual review",
      "Audit: 74/100 Needs review",
      "Safety: 34/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "parallel-web-parallel-data-enrichment (parallel-data-enrichment)",
      "install_command": "npx skills add parallel-web/parallel-agent-skills --skill parallel-data-enrichment",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "parallel-web-parallel-data-enrichment",
      "task": "Use parallel-data-enrichment in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/parallel-web-parallel-data-enrichment",
    "api": "https://www.openagentskill.com/api/agent/skills/parallel-web-parallel-data-enrichment",
    "audit": "https://www.openagentskill.com/skills/parallel-web-parallel-data-enrichment/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=parallel-web-parallel-data-enrichment&task=Use%20parallel-data-enrichment%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20parallel-data-enrichment%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20parallel-data-enrichment%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/parallel-web-parallel-data-enrichment/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/parallel-web-parallel-data-enrichment"
  }
}

创作者工具

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此列表来自公开来源，维护者认领获批前不会标记为官方。

创作者: parallel
来源: parallel-web/parallel-agent-skills
收录方: OpenAgentSkill 社区索引

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这条 Registry 收录列表归属于 parallel，但尚未标记为官方。认领后可增加已验证所有者信号，使后续发布、安装和审计更新更值得信赖。

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