Fähigkeiten datadata-api
📦

datadata-api

Inhaltsrevision r1 Hohes Risiko ⚙️ Externe Befehle🌐 Netzwerkzugriff📁 Dateisystemzugriff🔑 Umgebungsvariablen

Datadata-Quellen abfragen

Teams benötigen eine sicherere Möglichkeit, Datadata-Quellen zu prüfen, ohne eigene API-Aufrufe zu erstellen. Diese Skill bietet geführte CLI-Workflows für Metadaten, SQL-Ausführung, Exporte und die Verwaltung von Data-Space-Tabellen.

Unterstützt: Claude Codex Code(CC)
⚠️ 38 Schlecht

Mit meinem Agent installieren

Kopieren Sie diese Anfrage in Ihren Agent. Sie enthält die maßgebliche Skill-Seite und das Manifest.

Agent-Anfrage
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.

Ihr Agent sollte weiterhin seinen Plan anzeigen und alle von der Sicherheitsrichtlinie verlangten Bestätigungen anfordern.

Agent-lesbare Ressourcen

Verwenden Sie diese Links, wenn ein KI-Agent, Crawler oder Skript sauberen Kontext benötigt, statt die vollständige Seite zu lesen.

Markdown-Detailseite GET /skills/datadata-team-datadata-api.md Signiertes manifest GET /api/skills/datadata-team-datadata-api/manifest Signiertes lockfile GET /api/skills/datadata-team-datadata-api/lockfile

Testen

„datadata-api“ wird verwendet. Search Datadata for customer datasources.

Erwartetes Ergebnis:

Eine nummerierte Liste passender Quellen mit Namen, Eigentümern, Sichtbarkeit und Quellentyp zur Bestätigung durch den Benutzer.

„datadata-api“ wird verwendet. Run a sales summary query and fetch the result.

Erwartetes Ergebnis:

Die Ausführungs-ID, der gespeicherte Dateipfad, das Format, die Byte-Anzahl, die Zeilenanzahl und ein vorgeschlagener Vorschau-Befehl.

„datadata-api“ wird verwendet. Create a products table in my ducklake data space.

Erwartetes Ergebnis:

Eine knappe Bestätigung, dass die Tabelle erstellt wurde, gefolgt von der nächsten sicheren insert- oder describe-Aktion.

Sicherheitsaudit

Hohes Risiko
v4 • 6.7.2026 Versionsbericht öffnen

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
Gescannte Dateien
2,698
Analysierte Zeilen
46
Prüfelemente
0
Falschmeldungen ignoriert

Bestätigte Sicherheitsbedenken (3)

Hoch
scripts/datadata_query.py:600-611scripts/datadata_query.py:717-724
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.
Hoch
scripts/datadata_query.py:349-357scripts/datadata_query.py:571-573scripts/datadata_query.py:625-628
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.
Mittel
scripts/datadata_query.py:821-832scripts/datadata_query.py:928-932
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.
Elemente der Fähigkeitsprüfung (46)

Dies sind echte lokale Fähigkeiten, die für diese Fähigkeit erwartet werden können; daher müssen sie überprüft werden, werden jedoch nicht als bestätigtes bösartiges Verhalten gezählt.

Hoch
references/api.md:530
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.
Hoch
references/cli.md:20
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.
Hoch
references/cli.md:33
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.
Hoch
scripts/datadata_query.py:370
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.
Hoch
scripts/datadata_query.py:370
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.
Hoch
scripts/datadata_query.py:432
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.
Hoch
scripts/datadata_query.py:27
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.
Hoch
scripts/datadata_query.py:1152
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.
Hoch
scripts/datadata_query.py:402
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.
Hoch
scripts/datadata_query.py:1178
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.
Hoch
scripts/datadata_query.py:27
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.
Hoch
scripts/datadata_query.py:33
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.
Hoch
scripts/datadata_query.py:293
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.
Hoch
scripts/datadata_query.py:294
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.
Hoch
scripts/datadata_query.py:318
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.
Hoch
scripts/datadata_query.py:334
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.
Hoch
scripts/datadata_query.py:397
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.
Hoch
scripts/datadata_query.py:402
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.
Hoch
scripts/datadata_query.py:420
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.
Hoch
scripts/datadata_query.py:423
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.
Hoch
scripts/datadata_query.py:429
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.
Hoch
scripts/datadata_query.py:432
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.
Hoch
scripts/datadata_query.py:600
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.
Hoch
scripts/datadata_query.py:603
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.
Hoch
scripts/datadata_query.py:608
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.
Hoch
scripts/datadata_query.py:611
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.
Hoch
scripts/datadata_query.py:696
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.
Hoch
scripts/datadata_query.py:709
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.
Hoch
scripts/datadata_query.py:718
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.
Hoch
scripts/datadata_query.py:1152
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.
Hoch
scripts/datadata_query.py:1176
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.
Mittel
references/cli.md:20
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.
Mittel
references/cli.md:33
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.
Mittel
scripts/datadata_query.py:459
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.
Mittel
scripts/datadata_query.py:831
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.
Mittel
scripts/datadata_query.py:391
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.
Niedrig
scripts/datadata_query.py:14
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.
Niedrig
scripts/datadata_query.py:298
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.
Niedrig
scripts/datadata_query.py:300
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.
Niedrig
scripts/datadata_query.py:316
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.
Niedrig
scripts/datadata_query.py:322
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.
Niedrig
scripts/datadata_query.py:332
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.
Niedrig
scripts/datadata_query.py:338
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.
Niedrig
scripts/datadata_query.py:23
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.
Niedrig
scripts/datadata_query.py:827
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.
Niedrig
scripts/datadata_query.py:23
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.

Risikofaktoren

⚙️ Externe Befehle (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
🌐 Netzwerkzugriff (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
📁 Dateisystemzugriff (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
🔑 Umgebungsvariablen (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
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Wissenschaftliche Zitate (APA · BibTeX · CFF)

APA-Zitat

datadata-team. (2026). datadata-api security audit report (audit version 4) [Author version unspecified]. Skillstore. https://skillstore.io/skills/datadata-team-datadata-api/audits/4

BibTeX-Zitat

@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

Warum dieser Score Evidenzvertrauen: Mittel
68
Architektur
85
Wartbarkeit
85
Inhalt
67
Gemeinschaft
83
Spezifikationskonformität

Was Sie erstellen können

Ein neues Dataset erkunden

Datasource-Metadaten prüfen, Tabellen auflisten und ausgewählte Schemas beschreiben, bevor SQL geschrieben wird.

Einen API-Workflow erstellen

Einen Datadata-REST- oder CLI-Ablauf für Abfragen, Exporte und Fehlerbehandlung generieren.

Daten in einen Space laden

Ducklake-Tabellen erstellen, vorbereitete Zeilen einfügen und das gespeicherte Tabellenschema prüfen.

Diese Prompts ausprobieren

Verfügbare Tabellen auflisten 
Use Datadata to list tables for datasource <id>. Show table names, schemas, and the next safe step.
Eine Tabelle beschreiben 
Describe table <table> in datasource <id> and explain the columns that matter for a simple query.
Eine read-only Abfrage ausführen 
Run a read-only Datadata SQL query for <question>. Confirm datasource bindings and return the execution ID.
Einen Data Space verwalten 
Create a ducklake data-space table for <dataset>, insert these rows, then describe the table after insertion.

Bewährte Praktiken

  • Die ausgewählte Datasource bestätigen, bevor Abfragen oder Schreibbefehle ausgeführt werden.
  • Datasource-Typ, Tabellen und Spalten prüfen, bevor SQL geschrieben wird.
  • API-Schlüssel in Umgebungsvariablen oder lokaler Konfiguration speichern, niemals in Prompts.

Vermeiden

  • Keine drop- oder insert-Befehle ohne ausdrückliche Zustimmung des Benutzers ausführen.
  • Keine vollständigen NDJSON- oder CSV-Exporte in den Modellkontext laden.
  • Keine API-Schlüssel an eine nicht verifizierte Basis-URL oder ein gemeinsam genutztes Befehlsprotokoll senden.

Häufig gestellte Fragen

Erfordert diese Skill einen Datadata-API-Schlüssel?
Zugriff auf private Datasources, Abfrageausführung, Exporte und Schreibvorgänge erfordern einen Datadata-API-Schlüssel.
Kann sie öffentliche Datasources ohne Anmeldung durchsuchen?
Ja. Die Suche nach öffentlichen Datasources kann ohne API-Schlüssel ausgeführt werden.
Kann sie Daten schreiben?
Ja. Sie kann ducklake-Data-Space-Tabellen erstellen, befüllen und löschen, wenn der Schlüssel Schreibberechtigung hat.
Wo werden Abfrageergebnisse gespeichert?
Ergebnisse werden in eine lokale Datei geschrieben, normalerweise unter dem temporären Systemverzeichnis, sofern kein Ausgabepfad angegeben wird.
Funktioniert sie mit Claude, Codex und Claude Code?
Ja. Der Bericht erklärt Unterstützung für Claude, Codex und Claude Code.
Was sollte ich vor dem Ausführen von SQL prüfen?
Prüfen Sie die Datasource, Tabellennamen, Spaltennamen, die Abfrage-Engine und ob das SQL read-only ist.

Entwicklerdetails

Lizenz

MIT

Skillstore-Revision

r1

Versionshinweis

Der Autor hat keine Version angegeben.

Repository

https://github.com/datadata-team/datadata-skills/tree/master/skills/datadata-api

Ref.

34f316ba14ef36c7a620fc09f2676d2429997a77

Aktualität der Wartung

23.7.2026

Nutzung

2 Downloads · 32 Aufrufe

Dateistruktur

📁 agents/

📄 openai.yaml

📁 references/

📄 api.md

📄 cli.md

📄 data-spaces.md

📄 query-guide.md

📁 scripts/

📄 datadata_query.py

📄 SKILL.md

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