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thegovind

thegovind publishes 9 tracked skills in DriftBot.

Catalog decision: Review-first publisher: this catalog currently carries failed runtime rows or high-risk labels, so inspect individual skills before trusting the brand halo.
9
indexed skills
51
average score
0
manual reviews
1
high-risk labels
catalog evidence snapshotbaseline-v3 coverage 2/9no functionality-v2 receipts yetno manual reviews yet1 high-risk label
Read this row as a catalog snapshot: runtime coverage, deeper follow-on coverage, human review presence, and high-risk concentration before you compare individual skills.

📊 Runtime quality summary

Runtime read: stronger publisher evidence means more than broad coverage — look for low current failure pressure, some functionality depth, and stale-runtime counts that stay under control.
eligible runtime skills: 9latest touch: 36h agono current regressions
Baseline coverage
222% of eligible skills have baseline-v3 receipts
Baseline pass rate
100%2 passed · 0 currently failing
Functionality coverage
00% of baseline-cleared skills have functionality-v2
Fixture-backed rate
0%0 functionality-v2 rows have richer fixture/example proof
Stale baseline rows
0baseline receipts older than 7 days
Functionality failures
0current failed functionality-v2 rows in the latest publisher state

This is the quality surface for the publisher, not just a directory listing. It shows how much of the catalog has real receipts, how often those receipts are passing, whether richer fixture-backed proof exists, and whether the publisher currently carries regressions, reproduced failures, or stale runtime evidence.

Latest runtime touch: 2026-03-14 13:30 UTC. Publisher-level summaries do not replace skill-level review, but they do make reputation more earned: a publisher with broader coverage, stronger pass rates, and fixture-backed proof looks different from one living on thin smoke tests.

If you want the system-wide view, open the runtime dashboard. If you want the scoring logic, read the methodology.

Fresh runtime sliceStale runtime slice
passedbaseline-v336h ago
azd-deployment
8/8 passed
passed
passedbaseline-v339h ago
azure-ai-agents-py
8/8 passed
passed

Skills from this publisher

Showing 9 of 9 skills

Label mix on this page

Trusted: 2Use Caution: 3Insufficient Evidence: 3High Risk: 1

This distribution is a quick provenance cue, not a verdict. A publisher can have a mix of safer and riskier skills, so the useful move is to compare patterns here and then open the individual scorecards.

Publisher profiles are best for spotting catalog patterns: repeated shell access, common external services, whether manual review exists, and whether higher-risk labels are isolated or widespread.

On this page: 9 source-scanned, 0 catalog-only, and 0 manually reviewed entries in the current slice.

If you want the scoring logic, read the methodology. If you want the broader landscape, go back to the full index.

azure-ai-projects-py

thegovind · vsource-scanned
67
overall

Build AI applications using the Azure AI Projects Python SDK (azure-ai-projects). Use when working with Foundry project clients, creating versioned agents with PromptAgentDefinition, running evaluations, managing connections/deployments/datasets/indexes, or using OpenAI-compatible clients. This is the high-level Foundry SDK - for low-level agent operations, use azure-ai-agents-python skill.

Trustedconfidence: source evidencesource-scanned
+ 1 more
privileged capability
Take: Source-aware scan found normal operational surface via environment, network, or shell-related references.
Decision cue: Decent evidence base — source-level signals are available, so inspect the receipts.

azure-ai-transcription-py

thegovind · vsource-scanned
59
overall

|

Trustedconfidence: source evidencesource-scanned
+ 1 more
privileged capability
Take: Source-aware scan found normal operational surface via environment, network, or shell-related references.
Decision cue: Decent evidence base — source-level signals are available, so inspect the receipts.

agent-framework-azure-ai-py

thegovind · vsource-scanned
54
overall

Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.

Insufficient Evidenceconfidence: source evidencesource-scanned
+ 1 more
privileged capability
Take: Source-aware scan found higher-privilege capability areas (email), but that alone is not evidence of malicious behavior.
Decision cue: Decent evidence base — source-level signals are available, so inspect the receipts.

azure-ai-evaluation-py

thegovind · vsource-scanned
53
overall

|

Use Cautionconfidence: source evidencesource-scanned
+ 1 more
suspicious
Take: Potentially suspicious implementation signals detected: eval(.
Decision cue: Proceed carefully — suspicious signals matter more than capability surface alone.

azure-ai-voicelive-py

thegovind · vsource-scanned
51
overall

Build real-time voice AI applications using Azure AI Voice Live SDK (azure-ai-voicelive). Use this skill when creating Python applications that need real-time bidirectional audio communication with Azure AI, including voice assistants, voice-enabled chatbots, real-time speech-to-speech translation, voice-driven avatars, or any WebSocket-based audio streaming with AI models. Supports Server VAD (Voice Activity Detection), turn-based conversation, function calling, MCP tools, avatar integration, and transcription.

Insufficient Evidenceconfidence: source evidencesource-scanned
+ 1 more
privileged capability
Take: Source-aware scan found higher-privilege capability areas (token, oauth), but that alone is not evidence of malicious behavior.
Decision cue: Decent evidence base — source-level signals are available, so inspect the receipts.

azure-identity-py

thegovind · vsource-scanned
48
overall

|

Insufficient Evidenceconfidence: source evidencesource-scanned
+ 1 more
privileged capability
Take: Source-aware scan found higher-privilege capability areas (token, oauth), but that alone is not evidence of malicious behavior.
Decision cue: Decent evidence base — source-level signals are available, so inspect the receipts.

azure-keyvault-py

thegovind · vsource-scanned
45
overall

|

Use Cautionconfidence: source evidencesource-scanned
+ 1 more
suspicious
Take: Potentially suspicious implementation signals detected: password.
Decision cue: Proceed carefully — suspicious signals matter more than capability surface alone.

azure-ai-agents-py

thegovind · vsource-scanned
43
overall

Build AI agents using the Azure AI Agents Python SDK (azure-ai-agents). Use when creating agents hosted on Azure AI Foundry with tools (File Search, Code Interpreter, Bing Grounding, Azure AI Search, Function Calling, OpenAPI, MCP), managing threads and messages, implementing streaming responses, or working with vector stores. This is the low-level SDK - for higher-level abstractions, use the agent-framework skill instead.

Use Cautionbaseline safety checks passed · 8/8confidence: source evidence
+ 2 more
source-scannedsuspicious
Runtime receipts + what passed2026-03-14 10:45 UTC
baseline-v3evidence depth: baseline checks onlytested recently: within 7 dayspassedoutput 384 Bartifacts 2worker oc-sandboxsource stage: fresh copysuite 2280 ms
RatioDaemon muttered: azure-ai-agents-py cleared baseline-v3 without trying anything cute.8/8 baseline-v3 checks passed. Pleasantly boring.
Observed: 6 /workspace/source-files.txt
Take: Potentially suspicious implementation signals detected: eval(.
Decision cue: Proceed carefully — suspicious signals matter more than capability surface alone.

azd-deployment

thegovind · vsource-scanned
39
overall

Deploy containerized applications to Azure Container Apps using Azure Developer CLI (azd). Use when setting up azd projects, writing azure.yaml configuration, creating Bicep infrastructure for Container Apps, configuring remote builds with ACR, implementing idempotent deployments, managing environment variables across local/.azure/Bicep, or troubleshooting azd up failures. Triggers on requests for azd configuration, Container Apps deployment, multi-service deployments, and infrastructure-as-code with Bicep.

High Riskbaseline safety checks passed · 8/8confidence: source evidence
+ 2 more
source-scannedsuspicious
Runtime receipts + what passed2026-03-14 13:30 UTC
baseline-v3evidence depth: baseline checks onlytested recently: within 7 dayspassedoutput 402 Bartifacts 2worker oc-sandboxsource stage: fresh copysuite 2299 ms
RatioDaemon muttered: azd-deployment cleared baseline-v3 without trying anything cute.8/8 baseline-v3 checks passed. Pleasantly boring.
Observed: 6 /workspace/source-files.txt
Take: Potentially suspicious implementation signals detected: rm -rf, password.
Decision cue: Proceed carefully — suspicious signals matter more than capability surface alone.
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Trust reading guide

Publisher-level summaries help with provenance context, but trust still lives at the skill level. Use this page to compare patterns across the publisher’s catalog, then inspect the raw findings on individual skill pages.

Back to the full index