Skills datadata-api
📦
datadata-api
Content revision r1 High Risk ⚙️ External commands🌐 Network access📁 Filesystem access🔑 Env variables
Query Datadata Sources
Teams need a safer way to inspect Datadata sources without building custom API calls. This skill provides guided CLI workflows for metadata, SQL execution, exports, and data-space table management.
Supports: Claude Codex Code(CC)
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Install with my Agent
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Agent request
Review the Skillstore skill "datadata-api" from https://skillstore.io/skills/datadata-team-datadata-api.md and its manifest at https://skillstore.io/api/skills/datadata-team-datadata-api/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "datadata-api". Search Datadata for customer datasources.
Expected outcome:
A numbered list of matching sources with names, owners, visibility, and source type for user confirmation.
Using "datadata-api". Run a sales summary query and fetch the result.
Expected outcome:
The execution ID, saved file path, format, byte count, row count, and suggested preview command.
Using "datadata-api". Create a products table in my ducklake data space.
Expected outcome:
A concise confirmation that the table was created, followed by the next safe insert or describe action.
Security Audit
High Riskv4 • 7/6/2026 Open versioned report
The skill is Datadata-focused and I found no prompt injection or hidden payloads. Most static alerts are false positives from markdown backticks, Chinese documentation, placeholders, and Datadata resource IDs. Confirmed issues involve authenticated network use, local credential storage, API key exposure in device-flow output, broad default permissions, and local result-file writes.
7
Files scanned
2,698
Lines analyzed
46
Review items
0
False positives ignored
Confirmed security concerns (3)
High
Full API Key Exposed In Device Flow Output
The device-flow completion path returns the full API key in command output, and a fallback path prints the key if saving fails. Command output can persist in logs or agent transcripts.
The code explicitly includes the key in printed output fields and fallback messages. This is direct credential disclosure, even though it occurs during a legitimate auth flow.
High
Broad Default Device Authorization Scope
The default device-flow key requests read, scan, replace-file, query execution, result access, and data-space write permissions for every authorization. Read-only workflows receive write-capable credentials.
The permission list is hardcoded and reused for both device-flow entry points. It includes write and replace-file scopes beyond many documented read-only tasks.
Medium
Unconstrained Result Artifact Write Path
The result download command writes to a user-supplied output path or a default path built from the execution ID. The execution ID is not sanitized before becoming part of a filesystem path.
The code joins the execution ID into a temp filename and then opens the resolved path for writing. Legitimate IDs are likely safe, but the CLI does not enforce that format.
Capability review items (46)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
High
Generic API/secret keys
print(f"获取到 API Key: {api_key}")
The API reference example prints the full API key after device-flow token exchange. This can teach users or agents to leak a newly issued credential into logs or chat transcripts.
High
Hidden file in home directory
3. `~/.config/datadata/datadata-api-skills/config.json` 配置文件
The CLI documentation describes persistent API key storage under a hidden config path. The documented 0600 permission reduces exposure, but this is still sensitive filesystem behavior.
High
Hidden file in home directory
5. API Key 自动保存到 `~/.config/datadata/datadata-api-skills/config.json`(Unix 权限 0600),后续直接使用,无需重复授权
The CLI documentation describes persistent API key storage under a hidden config path. The documented 0600 permission reduces exposure, but this is still sensitive filesystem behavior.
High
Hidden file in home directory
其他: ~/.config/datadata/datadata-api-skills
The script stores Datadata authentication material under a hidden user config directory. The Unix permission hardening helps, but persistent local secret storage remains sensitive.
High
Hidden file access
其他: ~/.config/datadata/datadata-api-skills
The script stores Datadata authentication material under a hidden user config directory. The Unix permission hardening helps, but persistent local secret storage remains sensitive.
High
Python file write/append
with open(API_KEY_CONFIG_FILE, "w", encoding="utf-8") as fh:
The script stores Datadata authentication material under a hidden user config directory. The Unix permission hardening helps, but persistent local secret storage remains sensitive.
High
Python environment access
default=os.environ.get("DATADATA_API_KEY") or load_api_key_from_config() or "",
The script reads DATADATA_API_KEY from the environment and uses it for authenticated requests. Environment-based secret access is expected but sensitive.
High
Python environment access
env_key = os.environ.get("DATADATA_API_KEY")
The script reads DATADATA_API_KEY from the environment and uses it for authenticated requests. Environment-based secret access is expected but sensitive.
High
Configuration library
api_key = config.get("apiKey") if isinstance(config, dict) else None
The script reads the saved apiKey value from the local config file. This is intentional credential loading, but it handles a reusable secret.
High
Configuration library
return config.get("apiKey") if isinstance(config, dict) else None
The script reads the saved apiKey value from the local config file. This is intentional credential loading, but it handles a reusable secret.
High
Generic API/secret keys
default=os.environ.get("DATADATA_API_KEY") or load_api_key_from_config() or "",
The script reads DATADATA_API_KEY from the environment and treats it as an authentication secret. This is legitimate configuration but still secret access.
High
Generic API/secret keys
parser.add_argument("--api-key", default=global_opts.api_key)
The script accepts or handles a Datadata API key as part of its authentication flow. This is expected but security-sensitive credential handling.
High
Generic API/secret keys
if api_key:
The script places the Datadata API key into request headers for outbound HTTP calls. This is required for authentication, but it is sensitive if the base URL is misconfigured.
High
Generic API/secret keys
headers["X-Datadata-Api-key"] = api_key
The script places the Datadata API key into request headers for outbound HTTP calls. This is required for authentication, but it is sensitive if the base URL is misconfigured.
High
Generic API/secret keys
headers={"X-Datadata-Api-key": api_key, "Accept": "*/*"},
The script places the Datadata API key into request headers for outbound HTTP calls. This is required for authentication, but it is sensitive if the base URL is misconfigured.
High
Generic API/secret keys
headers={"X-Datadata-Api-key": api_key, "Accept": "*/*"},
The script places the Datadata API key into request headers for outbound HTTP calls. This is required for authentication, but it is sensitive if the base URL is misconfigured.
High
Generic API/secret keys
with open(API_KEY_CONFIG_FILE, "r", encoding="utf-8") as fh:
The script reads or writes a persisted Datadata API key in the local config file. Local persistence is useful but creates a credential exposure surface.
High
Generic API/secret keys
api_key = config.get("apiKey") if isinstance(config, dict) else None
The script reads or writes a persisted Datadata API key in the local config file. Local persistence is useful but creates a credential exposure surface.
High
Generic API/secret keys
return api_key
The script reads or writes a persisted Datadata API key in the local config file. Local persistence is useful but creates a credential exposure surface.
High
Generic API/secret keys
def save_api_key_to_config(api_key: str) -> None:
The script reads or writes a persisted Datadata API key in the local config file. Local persistence is useful but creates a credential exposure surface.
High
Generic API/secret keys
"apiKey": api_key,
The script reads or writes a persisted Datadata API key in the local config file. Local persistence is useful but creates a credential exposure surface.
High
Generic API/secret keys
with open(API_KEY_CONFIG_FILE, "w", encoding="utf-8") as fh:
The script reads or writes a persisted Datadata API key in the local config file. Local persistence is useful but creates a credential exposure surface.
High
Generic API/secret keys
api_key = result.get("key")
The device-flow path receives and stores a newly issued Datadata API key. This is expected, but it handles a fresh reusable credential.
High
Generic API/secret keys
save_api_key_to_config(api_key)
The device-flow path receives and stores a newly issued Datadata API key. This is expected, but it handles a fresh reusable credential.
High
Generic API/secret keys
print(f"✅ 授权成功!API Key: {api_key}", file=sys.stderr)
The script can print or return the full Datadata API key in command output. That exposes a reusable credential to terminal logs, chat transcripts, or command capture.
High
Generic API/secret keys
"提示:可通过 export DATADATA_API_KEY='{}' 手动设置。".format(api_key),
The script can print or return the full Datadata API key in command output. That exposes a reusable credential to terminal logs, chat transcripts, or command capture.
High
Generic API/secret keys
api_key = result.get("key")
The device-flow path receives and stores a newly issued Datadata API key. This is expected, but it handles a fresh reusable credential.
High
Generic API/secret keys
save_api_key_to_config(api_key)
The device-flow path receives and stores a newly issued Datadata API key. This is expected, but it handles a fresh reusable credential.
High
Generic API/secret keys
"key": api_key,
The script can print or return the full Datadata API key in command output. That exposes a reusable credential to terminal logs, chat transcripts, or command capture.
High
Generic API/secret keys
env_key = os.environ.get("DATADATA_API_KEY")
The script reads DATADATA_API_KEY from the environment and treats it as an authentication secret. This is legitimate configuration but still secret access.
High
Generic API/secret keys
with open(API_KEY_CONFIG_FILE, "r", encoding="utf-8") as fh:
The script reads or writes a persisted Datadata API key in the local config file. Local persistence is useful but creates a credential exposure surface.
Medium
Hidden file access
3. `~/.config/datadata/datadata-api-skills/config.json` 配置文件
The CLI documentation describes persistent API key storage under a hidden config path. The documented 0600 permission reduces exposure, but this is still sensitive filesystem behavior.
Medium
Hidden file access
5. API Key 自动保存到 `~/.config/datadata/datadata-api-skills/config.json`(Unix 权限 0600),后续直接使用,无需重复授权
The CLI documentation describes persistent API key storage under a hidden config path. The documented 0600 permission reduces exposure, but this is still sensitive filesystem behavior.
Medium
Python file write/append
with open(DEVICE_FLOW_STATE_FILE, "w", encoding="utf-8") as fh:
The script creates or writes Datadata config, device-flow state, or result files on disk. This is intended behavior, but it can persist sensitive data or overwrite files if misused.
Medium
Python file write/append
with open(path, "wb") as fh:
The script creates or writes Datadata config, device-flow state, or result files on disk. This is intended behavior, but it can persist sensitive data or overwrite files if misused.
Medium
Python os file operations
os.makedirs(API_KEY_CONFIG_DIR, mode=0o700, exist_ok=True)
The script creates or writes Datadata config, device-flow state, or result files on disk. This is intended behavior, but it can persist sensitive data or overwrite files if misused.
Low
Python HTTP libraries
import urllib.request
The Python CLI performs real HTTP requests to the configured Datadata base URL. This is intended behavior, but it transmits queries, metadata requests, and authenticated headers over the network.
Low
Python HTTP libraries
req = urllib.request.Request(url, data=data, headers=headers, method=method)
The Python CLI performs real HTTP requests to the configured Datadata base URL. This is intended behavior, but it transmits queries, metadata requests, and authenticated headers over the network.
Low
Python HTTP libraries
with urllib.request.urlopen(req) as resp:
The Python CLI performs real HTTP requests to the configured Datadata base URL. This is intended behavior, but it transmits queries, metadata requests, and authenticated headers over the network.
Low
Python HTTP libraries
req = urllib.request.Request(
The Python CLI performs real HTTP requests to the configured Datadata base URL. This is intended behavior, but it transmits queries, metadata requests, and authenticated headers over the network.
Low
Python HTTP libraries
with urllib.request.urlopen(req) as resp:
The Python CLI performs real HTTP requests to the configured Datadata base URL. This is intended behavior, but it transmits queries, metadata requests, and authenticated headers over the network.
Low
Python HTTP libraries
req = urllib.request.Request(
The Python CLI performs real HTTP requests to the configured Datadata base URL. This is intended behavior, but it transmits queries, metadata requests, and authenticated headers over the network.
Low
Python HTTP libraries
with urllib.request.urlopen(req) as resp:
The Python CLI performs real HTTP requests to the configured Datadata base URL. This is intended behavior, but it transmits queries, metadata requests, and authenticated headers over the network.
Low
Hardcoded URL
default=os.environ.get("DATADATA_BASE_URL", "https://www.datadata.com"),
The Python CLI performs real HTTP requests to the configured Datadata base URL. This is intended behavior, but it transmits queries, metadata requests, and authenticated headers over the network.
Low
Temp file creation
return os.path.join(tempfile.gettempdir(), f"datadata-{execution_id}{suffix}")
The result download path is built in the system temp directory by default. This is expected for exports, but it still writes data artifacts to local storage.
Low
Python environment access
default=os.environ.get("DATADATA_BASE_URL", "https://www.datadata.com"),
The script reads DATADATA_BASE_URL from the environment, which controls the remote endpoint. This is intended for configuration, but a bad value can redirect requests.
Risk Factors
⚙️ External commands (36)
agents/openai.yaml:9 agents/openai.yaml:11 agents/openai.yaml:13 agents/openai.yaml:17 agents/openai.yaml:21 agents/openai.yaml:25 SKILL.md:12 SKILL.md:14 SKILL.md:21 SKILL.md:25 SKILL.md:29 SKILL.md:49 SKILL.md:50 SKILL.md:51 SKILL.md:57 SKILL.md:58 SKILL.md:60 SKILL.md:64 SKILL.md:79 SKILL.md:83 SKILL.md:87 SKILL.md:88 SKILL.md:89 SKILL.md:106 SKILL.md:113 SKILL.md:114 SKILL.md:115 SKILL.md:116 SKILL.md:117 SKILL.md:121 SKILL.md:125 SKILL.md:126 SKILL.md:128 SKILL.md:132 SKILL.md:133 SKILL.md:136
🌐 Network access (39)
agents/openai.yaml:13 references/api.md:24 references/api.md:75 references/api.md:94 references/api.md:115 references/api.md:150 references/api.md:202 references/api.md:233 references/api.md:274 references/api.md:355 references/api.md:386 references/api.md:413 references/api.md:456 references/api.md:501 references/api.md:527 references/api.md:565 references/api.md:14 references/api.md:19 references/api.md:29 references/api.md:30 references/api.md:302 references/api.md:303 references/api.md:22 references/cli.md:43 references/cli.md:59 references/cli.md:43 references/cli.md:59 references/data-spaces.md:45 scripts/datadata_query.py:14 scripts/datadata_query.py:298 scripts/datadata_query.py:300 scripts/datadata_query.py:316 scripts/datadata_query.py:322 scripts/datadata_query.py:332 scripts/datadata_query.py:338 scripts/datadata_query.py:23 scripts/datadata_query.py:1339 SKILL.md:29 SKILL.md:58
📁 Filesystem access (19)
references/api.md:301 references/api.md:312 references/cli.md:20 references/cli.md:33 references/cli.md:37 references/cli.md:20 references/cli.md:33 references/cli.md:37 scripts/datadata_query.py:370 scripts/datadata_query.py:370 scripts/datadata_query.py:10 scripts/datadata_query.py:827 scripts/datadata_query.py:432 scripts/datadata_query.py:459 scripts/datadata_query.py:831 scripts/datadata_query.py:391 scripts/datadata_query.py:437 scripts/datadata_query.py:443 scripts/datadata_query.py:496
🔑 Env variables (130)
references/api.md:21 references/api.md:25 references/api.md:233 references/api.md:302 references/api.md:529 references/api.md:530 references/cli.md:10 references/cli.md:19 references/cli.md:42 references/cli.md:58 scripts/datadata_query.py:23 scripts/datadata_query.py:27 scripts/datadata_query.py:373 scripts/datadata_query.py:1152 scripts/datadata_query.py:402 scripts/datadata_query.py:407 scripts/datadata_query.py:1178 scripts/datadata_query.py:27 scripts/datadata_query.py:33 scripts/datadata_query.py:179 scripts/datadata_query.py:181 scripts/datadata_query.py:186 scripts/datadata_query.py:191 scripts/datadata_query.py:196 scripts/datadata_query.py:206 scripts/datadata_query.py:210 scripts/datadata_query.py:213 scripts/datadata_query.py:220 scripts/datadata_query.py:231 scripts/datadata_query.py:239 scripts/datadata_query.py:252 scripts/datadata_query.py:260 scripts/datadata_query.py:267 scripts/datadata_query.py:275 scripts/datadata_query.py:282 scripts/datadata_query.py:289 scripts/datadata_query.py:293 scripts/datadata_query.py:294 scripts/datadata_query.py:315 scripts/datadata_query.py:318 scripts/datadata_query.py:331 scripts/datadata_query.py:334 scripts/datadata_query.py:360 scripts/datadata_query.py:363 scripts/datadata_query.py:381 scripts/datadata_query.py:382 scripts/datadata_query.py:385 scripts/datadata_query.py:390 scripts/datadata_query.py:391 scripts/datadata_query.py:394 scripts/datadata_query.py:397 scripts/datadata_query.py:402 scripts/datadata_query.py:403 scripts/datadata_query.py:414 scripts/datadata_query.py:415 scripts/datadata_query.py:420 scripts/datadata_query.py:423 scripts/datadata_query.py:429 scripts/datadata_query.py:432 scripts/datadata_query.py:437 scripts/datadata_query.py:440 scripts/datadata_query.py:443 scripts/datadata_query.py:501 scripts/datadata_query.py:506 scripts/datadata_query.py:567 scripts/datadata_query.py:579 scripts/datadata_query.py:586 scripts/datadata_query.py:600 scripts/datadata_query.py:601 scripts/datadata_query.py:603 scripts/datadata_query.py:605 scripts/datadata_query.py:608 scripts/datadata_query.py:611 scripts/datadata_query.py:614 scripts/datadata_query.py:623 scripts/datadata_query.py:638 scripts/datadata_query.py:646 scripts/datadata_query.py:696 scripts/datadata_query.py:697 scripts/datadata_query.py:709 scripts/datadata_query.py:710 scripts/datadata_query.py:718 scripts/datadata_query.py:780 scripts/datadata_query.py:795 scripts/datadata_query.py:809 scripts/datadata_query.py:816 scripts/datadata_query.py:818 scripts/datadata_query.py:849 scripts/datadata_query.py:850 scripts/datadata_query.py:863 scripts/datadata_query.py:883 scripts/datadata_query.py:890 scripts/datadata_query.py:899 scripts/datadata_query.py:911 scripts/datadata_query.py:963 scripts/datadata_query.py:975 scripts/datadata_query.py:983 scripts/datadata_query.py:1000 scripts/datadata_query.py:1005 scripts/datadata_query.py:1008 scripts/datadata_query.py:1032 scripts/datadata_query.py:1047 scripts/datadata_query.py:1097 scripts/datadata_query.py:1100 scripts/datadata_query.py:1107 scripts/datadata_query.py:1126 scripts/datadata_query.py:1143 scripts/datadata_query.py:1145 scripts/datadata_query.py:1148 scripts/datadata_query.py:1149 scripts/datadata_query.py:1152 scripts/datadata_query.py:1153 scripts/datadata_query.py:1157 scripts/datadata_query.py:1162 scripts/datadata_query.py:1176 scripts/datadata_query.py:1221 scripts/datadata_query.py:1222 scripts/datadata_query.py:1224 scripts/datadata_query.py:1228 scripts/datadata_query.py:1271 scripts/datadata_query.py:1279 scripts/datadata_query.py:1310 scripts/datadata_query.py:1328 scripts/datadata_query.py:1342 scripts/datadata_query.py:1348 scripts/datadata_query.py:1349 scripts/datadata_query.py:1355 scripts/datadata_query.py:1358 scripts/datadata_query.py:1362 SKILL.md:57
Audited by: codex View Audit History →
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APA citation
datadata-team. (2026). datadata-api security audit report (audit version 4) [Author version unspecified]. Skillstore. https://skillstore.io/skills/datadata-team-datadata-api/audits/4BibTeX citation
@techreport{datadata-team-datadata-team-datadata-api-2026,
author = {datadata-team},
title = {datadata-api security audit report (audit version 4)},
institution = {Skillstore},
year = {2026},
number = {4},
url = {https://skillstore.io/skills/datadata-team-datadata-api/audits/4},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "datadata-api security audit report (audit version 4)"
version: "unspecified"
type: report
authors:
- name: "datadata-team"
date-released: "2026-07-06"
url: "https://skillstore.io/skills/datadata-team-datadata-api/audits/4"
identifiers:
- type: other
value: "skillstore:datadata-team-datadata-api:audit:4"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: Medium 68
Architecture
85
Maintainability
85
Content
67
Community
83
Spec Compliance
What You Can Build
Explore a New Dataset
Inspect datasource metadata, list tables, and describe selected schemas before writing SQL.
Build an API Workflow
Generate a Datadata REST or CLI flow for queries, exports, and error handling.
Load Data Into a Space
Create ducklake tables, insert prepared rows, and verify the stored table schema.
Try These Prompts
List Available Tables
Use Datadata to list tables for datasource <id>. Show table names, schemas, and the next safe step.
Describe One Table
Describe table <table> in datasource <id> and explain the columns that matter for a simple query.
Run a Read-Only Query
Run a read-only Datadata SQL query for <question>. Confirm datasource bindings and return the execution ID.
Manage a Data Space
Create a ducklake data-space table for <dataset>, insert these rows, then describe the table after insertion.
Best Practices
- Confirm the selected datasource before running queries or write commands.
- Inspect datasource type, tables, and columns before writing SQL.
- Keep API keys in environment variables or local config, never in prompts.
Avoid
- Do not run drop or insert commands without explicit user approval.
- Do not load full NDJSON or CSV exports into model context.
- Do not send API keys to an unverified base URL or shared command log.
Frequently Asked Questions
Does this skill require a Datadata API key?
Private datasource access, query execution, exports, and write operations require a Datadata API key.
Can it search public datasources without login?
Yes. Public datasource search can run without an API key.
Can it write data?
Yes. It can create, insert into, and drop ducklake data-space tables when the key has write permission.
Where are query results stored?
Results are written to a local file, usually under the system temp directory unless an output path is supplied.
Does it work with Claude, Codex, and Claude Code?
Yes. The report declares support for Claude, Codex, and Claude Code.
What should I verify before running SQL?
Verify the datasource, table names, column names, query engine, and that the SQL is read-only.