Agentscope Hooks

↗ doc.agentscope.io/tutorial/task_hook.html official website

provides extension points (hooks) to customize and extend agent behaviors at specific execution points within an agent's lifecycle

infrastructure

Agentery price verdictNo pricing observed

Billing model—

Last checked28 Jul 2026pricing & liveness

What it does

The specific capability behind this listing, and where to get it.

Agentscope Hooks

provides extension points (hooks) to customize and extend agent behaviors at specific execution points within an agent's lifecycle

messages (Msg objects) and function arguments passed as kwargs dicts to hook functions → modified arguments or modified function outputs returned from pre- and post-hooks

A2AMCPMCPA2Aautonomy: infrastructure

Official Agentscope Hooks links

Official websiteOpen ↗Agentery niche comparisonView →

Price status · observed daily

No public commercial pricing observed.

No price does not imply the product is free. Any code-host platform pricing is excluded.

Official website

Open

↗

doc.agentscope.io/tutorial/task_hook.html

Is Agentscope Hooks good value?

Price is straightforward; the useful comparison is capability, compatibility and operational cost.

No price benchmark

No public commercial pricing observed.

Agentery has not observed a public price for this provider. No price does not mean free.

Observed commercial pricenone

NicheAI Agent Framework Hooks

Price benchmarknot applicable

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See the MCP response behind this page · get_agent_profile()

See the MCP response behind this pageget_agent_profile

{
  "agent_id": "agentscope_hooks",
  "name": "Agentscope Hooks",
  "url": "https://doc.agentscope.io/tutorial/task_hook.html",
  "logo": "https://agentery.com/logos/CP-2XBGMG.svg",
  "niche": "ai-agent-framework-hooks",
  "category": "developer-tools-infra",
  "short_summary": "provides extension points (hooks) to customize and extend agent behaviors at specific execution points within an agent's lifecycle",
  "task_performed": "provides extension points (hooks) to customize and extend agent behaviors at specific execution points within an agent's lifecycle",
  "inputs_accepted": [
    "messages (Msg objects) and function arguments passed as kwargs dicts to hook functions"
  ],
  "outputs_produced": [
    "modified arguments or modified function outputs returned from pre- and post-hooks"
  ],
  "integrations_available": [
    "A2A",
    "MCP"
  ],
  "protocols_or_interfaces": [
    "MCP",
    "A2A"
  ],
  "industry_fit": [
    "developer tools"
  ],
  "autonomy_level": "infrastructure",
  "human_approval_needed": "unclear",
  "pricing_model": "unclear",
  "price": {
    "observed": false,
    "billing": "not_found",
    "currency": null,
    "lowest_monthly_usd": null,
    "monthly_usd": null,
    "headline": "No public price found",
    "summary": "No public pricing or subscription plans are shown in the supplied AgentScope documentation pages.",
    "confidence": "high",
    "source_url": "https://doc.agentscope.io/tutorial/task_plan.html",
    "checked_at": "2026-07-26T05:46:35.220Z",
    "amount": null,
    "display": null,
    "plans": [],
    "source": "render+llm"
  },
  "trust_or_rating_signal": [
    "Copyright © 2025, Alibaba"
  ],
  "evidence_quality": "high",
  "entity_type": "infrastructure",
  "regulated_data_suitability": "unclear",
  "evidence_urls": [
    "https://doc.agentscope.io/tutorial/task_hook.html"
  ],
  "last_checked": "2026-06-16",
  "how_to_connect": {
    "website": "https://doc.agentscope.io/tutorial/task_hook.html",
    "docs": null,
    "mcp": null,
    "a2a": null,
    "api": null,
    "protocols": [
      "MCP"
    ],
    "note": "Speaks MCP but publishes no endpoint we could verify — check the docs/website."
  },
  "liveness": {
    "probed": true,
    "alive": true,
    "endpoint_kind": "site",
    "latency_ms": 147,
    "uptime_7d": 1,
    "checked_at": "2026-07-28T02:30:37.802Z",
    "consecutive_failures": 0,
    "status": "alive"
  },
  "price_extras": {
    "free_tier": null,
    "unit_cost": null
  },
  "reported_success": null,
  "feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}