{
  "schema_version": "1.1",
  "id": "atlas-tool-use",
  "slug": "tool-use",
  "title": "Tool Use",
  "url": "https://feed7.dev/atlas/tool-use",
  "current_answer": null,
  "implementation_consequence": null,
  "agent_context": null,
  "confidence": "auto_collected",
  "last_verified": null,
  "last_updated": null,
  "evidence": [
    {
      "schema_version": "1.1",
      "id": "p8",
      "slug": "openai-structured-tool-use",
      "url": "https://feed7.dev/p/openai-structured-tool-use",
      "title": "OpenAI ships strict structured outputs for parallel tool use",
      "why_included": "Parallel tool calls now validate against JSON schema before execution — a whole class of agent failures disappears.",
      "summary": "Strict mode extends to parallel tool calls: every call is schema-validated pre-execution, with a repair pass on failure. Available in the API and Codex.",
      "practical_implication": "Delete your hand-rolled tool-call validators. Turn on strict mode and move validation effort to eval coverage instead.",
      "agent_context": "OpenAI strict structured outputs now cover parallel tool calls. Schema-validated pre-execution with one repair pass. Remove custom validators; rely on strict mode + evals.",
      "source": {
        "name": "OpenAI",
        "url": "https://openai.com/blog/structured-outputs-parallel-tools",
        "published_at": "2026-07-01T00:00:00.000Z"
      },
      "source_class": "blog_post",
      "content_type": "Official Release",
      "layer": "model",
      "domains": [
        "coding"
      ],
      "topics": [
        "tool-use"
      ],
      "verification": {
        "status": "official_source",
        "label": "Official Source",
        "method": "source_feed",
        "verified_at": null
      },
      "uncertainty": [],
      "connected_context": null,
      "lifecycle": "New",
      "published_at": "2026-07-01T00:00:00.000Z",
      "modified_at": "2026-07-01T00:00:00.000Z",
      "supersedes": [],
      "expires_at": null,
      "formats": {
        "html": "https://feed7.dev/p/openai-structured-tool-use",
        "json": "https://feed7.dev/p/openai-structured-tool-use.json",
        "markdown": "https://feed7.dev/p/openai-structured-tool-use.md"
      }
    },
    {
      "schema_version": "1.1",
      "id": "auto-f834153d50",
      "slug": "vercel-mcp-can-now-deploy-code-f834153d50",
      "url": "https://feed7.dev/p/vercel-mcp-can-now-deploy-code-f834153d50",
      "title": "Vercel MCP can now deploy code",
      "why_included": "Make deployment an explicit reviewed final step, and verify the background build rather than treating a returned URL as completion.",
      "summary": "Vercel’s MCP server can deploy agent-built code to new or existing projects and return a shareable URL, extending chat-based coding workflows through delivery.",
      "practical_implication": "Builders using Claude, Cursor, or another MCP client can make deployment an explicit final agent step, but should preserve review and permission boundaries before shipping generated changes.",
      "agent_context": "The Vercel MCP server now exposes **deploy_to_vercel** for deployment to **new or existing projects**. It detects the framework, installs dependencies, builds the code, and returns a shareable URL while the build continues.\n\nBuilders using Claude, Cursor, or another MCP client can make deployment an explicit final agent step, but should preserve review and permission boundaries before shipping generated changes.\n\nThe material does not describe approval controls, rollback behavior, failure handling, or which project settings the tool may change. A returned URL can precede completion of the background build.",
      "source": {
        "name": "Vercel",
        "url": "https://vercel.com/changelog/vercel-mcp-can-now-deploy-code",
        "published_at": "2026-07-23T00:00:00.000Z"
      },
      "source_class": "blog_post",
      "content_type": "Engineering Post",
      "layer": "infra",
      "domains": [
        "coding"
      ],
      "topics": [
        "mcp",
        "tool-use",
        "cloud-agents"
      ],
      "verification": {
        "status": "official_source",
        "label": "Official Source",
        "method": "source_feed",
        "verified_at": null
      },
      "uncertainty": [],
      "connected_context": null,
      "lifecycle": "New",
      "published_at": "2026-07-23T00:00:00.000Z",
      "modified_at": "2026-07-23T00:00:00.000Z",
      "supersedes": [],
      "expires_at": null,
      "formats": {
        "html": "https://feed7.dev/p/vercel-mcp-can-now-deploy-code-f834153d50",
        "json": "https://feed7.dev/p/vercel-mcp-can-now-deploy-code-f834153d50.json",
        "markdown": "https://feed7.dev/p/vercel-mcp-can-now-deploy-code-f834153d50.md"
      }
    },
    {
      "schema_version": "1.1",
      "id": "auto-be3ca53745",
      "slug": "gemini-api-managed-agents-3-6-flash-hooks-and-more-be3ca53745",
      "url": "https://feed7.dev/p/gemini-api-managed-agents-3-6-flash-hooks-and-more-be3ca53745",
      "title": "Gemini API Managed Agents: 3.6 Flash, hooks, and more",
      "why_included": "Use pre- and post-tool hooks for policy checks, and cap autonomous loops with max_total_tokens while preserving resumable state.",
      "summary": "Gemini Managed Agents now add model selection, sandbox hooks, token caps, schedules, and free-tier access, covering several controls needed for unattended coding work.",
      "practical_implication": "Add hooks where tool calls need policy checks, linting, or audit output, and set max_total_tokens on autonomous loops. A capped run pauses as incomplete while preserving its environment, so it can resume with a new budget and previous interaction ID.",
      "agent_context": "Gemini Managed Agents now default to **Gemini 3.6 Flash**. The service adds pre- and post-tool hooks, explicit model selection, scheduled triggers, free-tier access, environment management, and persistent files across scheduled runs.\n\nAdd hooks where tool calls need policy checks, linting, or audit output, and set **max_total_tokens** on autonomous loops. A capped run pauses as incomplete while preserving its environment, so it can resume with a new budget and previous interaction ID.\n\nThe agent remains a preview identified as antigravity-preview-05-2026. Scheduled runs reuse a sandbox, which is useful for stateful work but makes cleanup, state drift, and hook failure behavior important operational concerns.",
      "source": {
        "name": "Google",
        "url": "https://blog.google/innovation-and-ai/technology/developers-tools/expanding-managed-agents-gemini-api-3-6-flash-hooks/",
        "published_at": "2026-07-28T00:00:00.000Z"
      },
      "source_class": "blog_post",
      "content_type": "Official Release",
      "layer": "tools",
      "domains": [
        "coding",
        "security"
      ],
      "topics": [
        "cloud-agents",
        "sandboxing",
        "tool-use"
      ],
      "verification": {
        "status": "official_source",
        "label": "Official Source",
        "method": "source_feed",
        "verified_at": null
      },
      "uncertainty": [],
      "connected_context": null,
      "lifecycle": "New",
      "published_at": "2026-07-28T00:00:00.000Z",
      "modified_at": "2026-07-28T00:00:00.000Z",
      "supersedes": [],
      "expires_at": null,
      "formats": {
        "html": "https://feed7.dev/p/gemini-api-managed-agents-3-6-flash-hooks-and-more-be3ca53745",
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        "markdown": "https://feed7.dev/p/gemini-api-managed-agents-3-6-flash-hooks-and-more-be3ca53745.md"
      }
    }
  ],
  "conflicting_sources": [],
  "superseded_claims": [],
  "corpus_evidence": [
    {
      "title": "MCP Apps: Extending the Frontier — Ido Salomon & Liad Yosef",
      "url": "https://www.youtube.com/watch?v=-jY2T2PiJBE",
      "source_name": "AI Engineer",
      "published_at": "2026-08-02T23:30:06+00:00",
      "summary": "MCP Apps let servers return sandboxed, interactive UI instead of text alone while the host retains control of prompts and tool calls—a useful pattern for agent workflows needing charts or controls."
    },
    {
      "title": "MCP Tasks (async): Why Aren't Any Agents Supporting Them? — Cornelia Davis, Temporal",
      "url": "https://www.youtube.com/watch?v=s4r6nk5WsZw",
      "source_name": "AI Engineer",
      "published_at": "2026-08-02T20:00:06+00:00",
      "summary": "MCP Tasks aim to make long-running tool calls durable across disconnects and crashes. The proposed V2 removes session-heavy state, but polling scale and implementation complexity remain unresolved."
    },
    {
      "title": "Learning on the Job: The Future of Post-Training — Raymond Feng, Applied Compute",
      "url": "https://www.youtube.com/watch?v=k35LeKZEhiE",
      "source_name": "AI Engineer",
      "published_at": "2026-07-31T22:30:06+00:00",
      "summary": "Training on a production harness could adapt an agent to real workflows, but non-replayable interactions break common RL assumptions and make feedback harder to turn into updates."
    },
    {
      "title": "Chat SDK now supports reactions and ephemeral messages on Teams",
      "url": "https://vercel.com/changelog/chat-sdk-reactions-and-ephemeral-messages-on-teams",
      "source_name": "Vercel",
      "published_at": "2026-07-31T00:00:00+00:00",
      "summary": "Chat SDK’s Teams adapter adds reactions, user-only ephemeral messages, custom token supply, and routing fixes useful for building safer agent approval and progress flows."
    },
    {
      "title": "Latest MCP spec now supported in mcp-handler",
      "url": "https://vercel.com/changelog/latest-mcp-spec-now-supported-in-mcp-handler",
      "source_name": "Vercel",
      "published_at": "2026-07-30T00:00:00+00:00",
      "summary": "mcp-handler 2.0 adds the stateless 2026 MCP protocol and SDK v2 while keeping 2025 Streamable HTTP clients working, but drops HTTP+SSE and raises upgrade requirements."
    },
    {
      "title": "Inkling Small from Thinking Machines is now available on AI Gateway",
      "url": "https://vercel.com/changelog/inkling-small-now-available-on-ai-gateway",
      "source_name": "Vercel",
      "published_at": "2026-07-30T00:00:00+00:00",
      "summary": "Inkling Small is pitched as a lower-compute model for coding, tool use, and visual reasoning, with adjustable thinking effort and zero-data-retention routing through Vercel AI Gateway."
    },
    {
      "title": "Project-scoped Tokens",
      "url": "https://vercel.com/changelog/project-scoped-tokens",
      "source_name": "Vercel",
      "published_at": "2026-07-30T00:00:00+00:00",
      "summary": "Vercel tokens can now be restricted to one project, giving agent jobs and automation read/write access without exposing unrelated project, team, or user resources."
    },
    {
      "title": "How Kepler Built Verifiable AI for Financial Services — Vinoo Ganesh",
      "url": "https://www.youtube.com/watch?v=Tt2kX2sgQio",
      "source_name": "AI Engineer",
      "published_at": "2026-07-29T21:00:06+00:00",
      "summary": "Kepler’s pattern keeps LLMs away from numeric mutation: agents choose sources and steps, while deterministic systems persist, calculate, and reject unverifiable values."
    },
    {
      "title": "Why Off-the-Shelf AI Doesn't Understand Money — Udi Menkes, Intuit",
      "url": "https://www.youtube.com/watch?v=Owb8g3yDyzo",
      "source_name": "AI Engineer",
      "published_at": "2026-07-29T20:00:06+00:00",
      "summary": "Intuit argues that domain context alone does not create experience. Its approach learns from verified state-action-outcome histories, using frontier models only to propose candidates."
    },
    {
      "title": "Grok Voice Think Fast 2.0 now available on AI Gateway",
      "url": "https://vercel.com/changelog/grok-voice-think-fast-2-0-now-available-on-ai-gateway",
      "source_name": "Vercel",
      "published_at": "2026-07-29T00:00:00+00:00",
      "summary": "Grok Voice Think Fast 2.0 brings speech-to-speech reasoning and earlier tool calls to Vercel’s realtime API, with server-minted tokens keeping gateway keys off clients."
    },
    {
      "title": "Why Large? Tiny LMs & Agents on Edge/Robotics — Cormac Brick, Google",
      "url": "https://www.youtube.com/watch?v=hacEQHHhu2Q",
      "source_name": "AI Engineer",
      "published_at": "2026-07-25T17:00:06+00:00",
      "summary": "Edge-agent design is often memory-bound: use small prompted models when devices can spare gigabytes, or fine-tune tiny models for narrow functions when reach and latency matter more."
    },
    {
      "title": "Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills",
      "url": "https://arxiv.org/abs/2607.22529v1",
      "source_name": "arXiv",
      "published_at": "2026-07-24T17:59:22+00:00",
      "summary": "Skill-SP turns agent skills into units for verifiable self-play: generate tasks, solve them, then update the skill library from execution feedback. The abstract provides no per-benchmark effect sizes."
    },
    {
      "title": "Perception Agents — Antje Barth, Amazon AGI Lab",
      "url": "https://www.youtube.com/watch?v=2JX6JYyQG4Y",
      "source_name": "AI Engineer",
      "published_at": "2026-07-23T16:00:06+00:00",
      "summary": "Perception agents share the rendered interface with users, turning visual annotations and design rules into agent input and checks. The open-source harness is an early attempt to close computer-use feedback loops."
    },
    {
      "title": "AI Gateway now supports streaming transcription",
      "url": "https://vercel.com/changelog/ai-gateway-now-supports-streaming-transcription",
      "source_name": "Vercel",
      "published_at": "2026-07-22T00:00:00+00:00",
      "summary": "AI Gateway can now stream audio into transcription models and emit partial text, letting text-based agents accept lower-latency voice input without changing the agent itself."
    },
    {
      "title": "Vercel MCP now supports purchases",
      "url": "https://vercel.com/changelog/vercel-mcp-now-supports-purchases",
      "source_name": "Vercel",
      "published_at": "2026-07-21T00:00:00+00:00",
      "summary": "Vercel MCP can now buy plans, credits, add-ons, and domains from an AI assistant, but it must disclose pricing and obtain confirmation before completing a charge."
    },
    {
      "title": "PalmClaw: A Native On-Device Agent Framework for Mobile Phones",
      "url": "https://arxiv.org/abs/2607.13027v1",
      "source_name": "arXiv",
      "published_at": "2026-07-14T17:58:57+00:00",
      "summary": "PalmClaw runs the agent loop, memory, skills, and tools directly on a phone, exposing device capabilities as structured calls instead of GUI gestures. The paper reports faster, more reliable task execution."
    },
    {
      "title": "Chat SDK adds X adapter support",
      "url": "https://vercel.com/changelog/chat-sdk-adds-x-adapter-support",
      "source_name": null,
      "published_at": null,
      "summary": "Chat SDK now targets X alongside six other channels from one bot codebase, handling webhook verification and OAuth refresh while accepting no streaming and likes-only reactions."
    },
    {
      "title": "alibaba/open-code-review",
      "url": "https://github.com/alibaba/open-code-review",
      "source_name": "GitHub",
      "published_at": null,
      "summary": "Alibaba’s open-source review CLI combines deterministic diff handling with an LLM agent to improve line-level precision and reduce token use, while explicitly trading away recall."
    },
    {
      "title": "chenyme/grok2api",
      "url": "https://github.com/chenyme/grok2api",
      "source_name": null,
      "published_at": null,
      "summary": "Grok2API fronts Grok Build, Web, and Console account pools with OpenAI- and Anthropic-compatible APIs, but its unofficial SSO routing creates terms, credential, and renewal risk."
    },
    {
      "title": "Muse Spark 1.1 is now available on AI Gateway",
      "url": "https://vercel.com/changelog/muse-spark-1-1-is-now-available-on-ai-gateway",
      "source_name": null,
      "published_at": null,
      "summary": "Muse Spark 1.1 gives agent builders a 1M-token multimodal model with parallel tool calls, MCP support, and the option to run as a main agent or subagent."
    },
    {
      "title": "Search Beyond What Can Be Taught: Evolving the Knowledge Boundary in Agentic Visual Generation",
      "url": "https://arxiv.org/abs/2607.05382v1",
      "source_name": null,
      "published_at": null,
      "summary": "SearchGen-Bench shows open image generators score 21–28/100 on long-tail entities, and naive search retrieval only adds noise; a teach-then-search co-training recipe learns when to retrieve versus rely on weights."
    },
    {
      "title": "Reasoning LLM Improves Speaker Recognition in Long-form TV Dramas",
      "url": "https://arxiv.org/abs/2607.02504v1",
      "source_name": null,
      "published_at": null,
      "summary": "DramaSR-532K benchmarks speaker attribution over 532K dialogue lines and 900+ TV-drama characters; a reasoning LLM with multimodal tool use beats acoustic baselines, especially on short utterances."
    },
    {
      "title": "Expanding Managed Agents in Gemini API: background tasks, remote MCP and more",
      "url": "https://blog.google/innovation-and-ai/technology/developers-tools/expanding-managed-agents-gemini-api/",
      "source_name": null,
      "published_at": null,
      "summary": "Gemini Managed Agents can now run asynchronously, connect to remote MCP servers, call client-side functions, and rotate credentials without losing sandbox state."
    },
    {
      "title": "WhiskeySockets/Baileys",
      "url": "https://github.com/WhiskeySockets/Baileys",
      "source_name": "GitHub",
      "published_at": null,
      "summary": "Baileys exposes WhatsApp Web through a WebSocket-based TypeScript API, but v7 introduces breaking changes and remains unofficial, making migration and platform risk the main concerns."
    },
    {
      "title": "ChromeDevTools/chrome-devtools-mcp",
      "url": "https://github.com/ChromeDevTools/chrome-devtools-mcp",
      "source_name": "GitHub",
      "published_at": null,
      "summary": "Chrome DevTools MCP gives coding agents direct access to browser automation, network data, console errors, screenshots, and performance traces, with privacy controls worth setting explicitly."
    },
    {
      "title": "zhaoxuya520/reverse-skill",
      "url": "https://github.com/zhaoxuya520/reverse-skill",
      "source_name": "GitHub",
      "published_at": null,
      "summary": "A security skill router gives coding agents scoped, repeatable playbooks for reverse engineering and pentesting instead of ad hoc tool selection. Its case workflow also preserves evidence and findings."
    },
    {
      "title": "github/copilot-sdk",
      "url": "https://github.com/github/copilot-sdk",
      "source_name": "GitHub",
      "published_at": null,
      "summary": "GitHub now exposes the Copilot CLI agent runtime as SDKs for six languages, including planning, tools, and file edits. Builders can embed it with configurable permissions, auth, models, and BYOK."
    },
    {
      "title": "Use any Chat SDK adapter with eve",
      "url": "https://vercel.com/changelog/eve-chat-sdk-channel",
      "source_name": null,
      "published_at": null,
      "summary": "eve’s Chat SDK channel lets one agent span messaging adapters while retaining threads, approval cards, proactive sends, webhook handling, and overridable defaults."
    },
    {
      "title": "In Code They Act, In Proof We Trust — Erik Meijer, Leibniz Labs",
      "url": "https://www.youtube.com/watch?v=-CnA2lGfymY",
      "source_name": null,
      "published_at": null,
      "summary": "A proposed agent harness separates planning from execution, represents tool calls as inspectable programs, and requires machine-checkable safety proofs before side effects run."
    },
    {
      "title": "Semantic Blindness: 500,000 Sensors Confused an LLM - Raahul Singh & Vanč Levstik, Phaidra",
      "url": "https://www.youtube.com/watch?v=EUsPvBeIx70",
      "source_name": null,
      "published_at": null,
      "summary": "Use LLMs to turn ambiguous requests into search plans, then resolve entities with deterministic indexes and set operations. This avoids context bloat and silent misses at production scale."
    },
    {
      "title": "Stop AI Agent Hallucinations: 5 Techniques + Production Patterns - Elizabeth Fuentes, AWS",
      "url": "https://www.youtube.com/watch?v=vJukHCIv7Ck",
      "source_name": null,
      "published_at": null,
      "summary": "Five code-level controls reduce agent errors: narrow tool context, query structured data, validate responses, enforce rules before calls, and steer runtime correction."
    },
    {
      "title": "Panniantong/Agent-Reach",
      "url": "https://github.com/Panniantong/Agent-Reach",
      "source_name": "GitHub",
      "published_at": null,
      "summary": "Agent Reach installs, checks, and routes web-access tools for coding agents, reducing the setup work behind research across social platforms, video sites, GitHub, RSS, and the open web."
    }
  ]
}