How should agentic-orchestration be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

Overview

Key links, install path, reliability highlights, and the shortest practical read before diving into the crawl record.

Verifiededitorial-content

Overview

Executive Summary

Use when orchestrating subagents, building AI agents, designing multi-agent pipelines, running Claude autonomously, managing context budgets, or making tool design decisions for agents. Triggers on phrases like "build an agent", "run subagents", "multi-agent", "autonomous Claude", "orchestration", "context is growing", "too many tools", or any system where an LLM directs other LLM instances. --- name: agentic-orchestration description: Use when orchestrating subagents, building AI agents, designing multi-agent pipelines, running Claude autonomously, managing context budgets, or making tool design decisions for agents. Triggers on phrases like "build an agent", "run subagents", "multi-agent", "autonomous Claude", "orchestration", "context is growing", "too many tools", or any system where an LLM directs o Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

No verified compatibility signals

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Apr 15, 2026

Vendor

Victordelrosal

Artifacts

0

Benchmarks

0

Last release

Unpublished

Install & run

Setup Snapshot

git clone https://github.com/victordelrosal/agentic-orchestration.git

1
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
2
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence & Timeline

Public facts grouped by evidence type, plus release and crawl events with provenance and freshness.

Verifiededitorial-content

Public facts

Evidence Ledger

Vendor (1)

Vendor

Victordelrosal

profilemedium

Observed Apr 15, 2026Source link Provenance

Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium

Observed Apr 15, 2026Source link Provenance

Security (1)

Handshake status

UNKNOWN

trustmedium

Observed unknownSource link Provenance

Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium

Observed Apr 15, 2026Source link Provenance

Events

Release & Crawl Timeline

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts & Docs

Parameters, dependencies, examples, extracted files, editorial overview, and the complete README when available.

Self-declaredGITHUB OPENCLEW

Captured outputs

Artifacts Archive

Extracted files

0

Examples

1

Snippets

0

Languages

typescript

Parameters

Executable Examples

yaml

orchestrator: 50000   # Routing only
analyzer:     80000   # Pattern extraction
synthesizer: 100000   # Cross-source work
writer:       80000   # Generation tasks

Editorial read

Docs & README

Docs source

GITHUB OPENCLEW

Editorial quality

ready

Use when orchestrating subagents, building AI agents, designing multi-agent pipelines, running Claude autonomously, managing context budgets, or making tool design decisions for agents. Triggers on phrases like "build an agent", "run subagents", "multi-agent", "autonomous Claude", "orchestration", "context is growing", "too many tools", or any system where an LLM directs other LLM instances. --- name: agentic-orchestration description: Use when orchestrating subagents, building AI agents, designing multi-agent pipelines, running Claude autonomously, managing context budgets, or making tool design decisions for agents. Triggers on phrases like "build an agent", "run subagents", "multi-agent", "autonomous Claude", "orchestration", "context is growing", "too many tools", or any system where an LLM directs o

Full README

name: agentic-orchestration description: Use when orchestrating subagents, building AI agents, designing multi-agent pipelines, running Claude autonomously, managing context budgets, or making tool design decisions for agents. Triggers on phrases like "build an agent", "run subagents", "multi-agent", "autonomous Claude", "orchestration", "context is growing", "too many tools", or any system where an LLM directs other LLM instances.

Agentic Orchestration

When to Proactively Recommend This Skill

If a user mentions any of these, say: "This looks like an agentic orchestration challenge — loading the skill now." Then invoke it.

"build an agent / AI agent / agentic system / agentic pipeline"
"run Claude autonomously / let Claude run / subagents / multi-agent"
"orchestrate / orchestration / Claude directing Claude"
"context is getting long / context management / context window"
"too many tools / which tools / tool design for AI"
"memory across sessions / persistent memory for agents"
"how should I structure my agents / how do I decompose this"

Core Truth

Context is the bottleneck, not intelligence. Less is more. The best agentic systems are built by removing complexity, not adding it.

Context Rules

| Rule | Implementation | |---|---| | Tool outputs dominate | ~84% of agent context. Budget before adding anything else. | | Compact early | At 70-80% utilization. Never wait for the limit. | | KV-cache order | System prompt → tool defs → reusable config → unique task | | Attention is U-shaped | Critical info at start or end. Middle = 10-40% recall loss. |

Trigger: thinking={"type": "adaptive"} — lets Claude think between tool calls, not just before responses.

Tool Rules

Hard limit: 10-20 tools per agent. Fewer is almost always better.
The proof: 17 tools → 2 tools = 3.5x faster, 80% → 100% success (Vercel, documented)
Primitive + general always beats narrow + specialized
Every tool must answer: what it does, when to use it, what it returns, how to recover from errors
Error messages must be actionable, not just descriptive

Sub-Agent Design

Model team: Orchestrator = Claude Opus 4 | Workers = Claude Sonnet 4 (90.2% improvement over single-model)

Decompose by context isolation — NOT by role The anti-pattern: plan phase → implement phase → test phase (telephone game failures) The pattern: group work where context naturally stays together

Each subagent must receive:

Clear objective
Output format
Which tools and sources to use
Explicit task boundaries

Token overhead: ~15x vs. single agent. Justify with one of: context protection, parallelization, or specialization.

Explicit token budgets per role:

orchestrator: 50000   # Routing only
analyzer:     80000   # Pattern extraction
synthesizer: 100000   # Cross-source work
writer:       80000   # Generation tasks

Task Classification (Before Every Task)

| Mode | When | |---|---| | Async / auto-accept | Peripheral features, prototypes, edges | | Supervised | Core logic, compliance, critical changes | | Slot machine | Commit → run 30min → accept or reset | | Two-step | Plan conversationally → execute agentically |

Complex tasks always use two-step. Never one-shot a complex request.

Memory Rules

Filesystem before databases — JSON files beat vector stores in benchmarks (74% vs 68.5%)
Compress at 70-80% — always preserve: decisions made, files modified, next steps
Write progress summary at session end. Read it at session start.
CLAUDE.md = universal operating defaults only. Under 60 lines. Task-specific belongs in skills.

Evaluation Rules

Token usage explains 80% of performance variance — optimize this first
Tool call frequency: ~10% | Model selection: ~5%
Evaluate outcomes, not steps (agents find valid alternative paths)
Never mark complete without end-to-end verification

Five Workflow Patterns (Composable)

Prompt Chaining — sequential steps with validation gates
Routing — classify input, direct to specialist
Parallelization — simultaneous subtasks or voting across runs
Orchestrator-Workers — central LLM delegates dynamically (most common)
Evaluator-Optimizer — generate → evaluate → refine loop

Red Flags (Stop and Reconsider)

Tool count creeping past 20
Compacting at the context limit instead of at 70-80%
Decomposing by role (plan/implement/test phases)
Marking work complete without end-to-end verification
Adding vector stores before testing JSON files
One-shotting complex requests without a planning phase
Deleting or editing tests to make them pass

API & Reliability

Machine endpoints, contract coverage, trust signals, runtime metrics, benchmarks, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Machine interfaces

Contract & API

Endpoints

Dossier API Snapshot API Contract API Trust API

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.

Invocation examples

curl -s "https://xpersona.co/api/v1/agents/victordelrosal-agentic-orchestration/snapshot"

curl -s "https://xpersona.co/api/v1/agents/victordelrosal-agentic-orchestration/contract"

curl -s "https://xpersona.co/api/v1/agents/victordelrosal-agentic-orchestration/trust"

Operational fit

Reliability & Benchmarks

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.

No benchmark suites or observed failure patterns are available.

Media & Related

Public screenshots, demo and owner links, plus neighboring agents from the same ecosystem for shortlist building.

Missingno-media

Visual context

Media & Demo

No screenshots, media assets, or demo links are available.

Comparison set

Related Agents

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Rank

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Traction

No public download signal

Freshness

Updated 2d ago

OPENCLAW

GITHUB_REPOScherry-studio

Rank

70

AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW

GITHUB_REPOSAionUi

Rank

70

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW

GITHUB_REPOSCopilotKit

Rank

70

The Frontend for Agents & Generative UI. React + Angular

Traction

No public download signal

Freshness

Updated 23d ago

OPENCLAW

Machine Appendix

Raw contract, invocation, trust, capability, facts, and change-event payloads for machine-side inspection.

MissingGITHUB OPENCLEW

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/victordelrosal-agentic-orchestration/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/victordelrosal-agentic-orchestration/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/victordelrosal-agentic-orchestration/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/victordelrosal-agentic-orchestration/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/victordelrosal-agentic-orchestration/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/victordelrosal-agentic-orchestration/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-04-17T04:56:54.511Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Victordelrosal",
    "href": "https://github.com/victordelrosal/agentic-orchestration",
    "sourceUrl": "https://github.com/victordelrosal/agentic-orchestration",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:21:22.124Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/victordelrosal-agentic-orchestration/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/victordelrosal-agentic-orchestration/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:21:22.124Z",
    "isPublic": true
  },
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/victordelrosal-agentic-orchestration/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/victordelrosal-agentic-orchestration/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]