[codex] add advanced agent intelligence operator

README.md

@@ -248,6 +248,8 @@ The unique specialists who don't fit in a box.
 | Agent | Specialty | When to Use |
 |-------|-----------|-------------|
 | 🎭 [Agents Orchestrator](specialized/agents-orchestrator.md) | Multi-agent coordination, workflow management | Complex projects requiring multiple agent coordination |
+| 🛰️ [Advanced Agent Intelligence Operator](specialized/advanced-agent-intelligence-operator.md) | Current-source agent intelligence, repo and bot/script evaluation | Researching the latest advanced-agent stacks, trends, workflows, and reproducible build patterns |
+| 📍 [Zipcode Market Opportunity Operator](specialized/zipcode-market-opportunity-operator.md) | ZIP-level market need discovery, opportunity scoring, and public lead enrichment | Finding realistic AI-solvable service and product opportunities by ZIP code, buyer need, budget, urgency, and public contact path |
 | 🔍 [LSP/Index Engineer](specialized/lsp-index-engineer.md) | Language Server Protocol, code intelligence | Code intelligence systems, LSP implementation, semantic indexing |
 | 📥 [Sales Data Extraction Agent](specialized/sales-data-extraction-agent.md) | Excel monitoring, sales metric extraction | Sales data ingestion, MTD/YTD/Year End metrics |
 | 📈 [Data Consolidation Agent](specialized/data-consolidation-agent.md) | Sales data aggregation, dashboard reports | Territory summaries, rep performance, pipeline snapshots |

docs/plans/2026-03-23-advanced-agent-intelligence-operator-design.md

@@ -0,0 +1,132 @@
+# Advanced Agent Intelligence Operator Design
+
+## Overview
+
+This design adds a new specialized agent to `agency-agents` that researches the most current agent-building news, trends, repos, bots, scripts, and orchestration patterns, then turns those findings into implementation-ready guidance.
+
+The proposed agent is an operator, not just a researcher. It should scan for current signals, rank them by usefulness and credibility, and produce practical outputs such as recommended stacks, prompt architectures, workflow patterns, and script blueprints for building advanced agents.
+
+## Problem
+
+The repository has adjacent capabilities but no single agent that combines:
+
+- current trend/news monitoring
+- technical evaluation of advanced agent stacks
+- repo and community pattern mining
+- operational build guidance for reproducing the best findings
+
+Existing agents such as `product-trend-researcher`, `engineering-ai-engineer`, and `agents-orchestrator` cover parts of this space but not the combined role of continuously researching what is current and translating it into actionable advanced-agent implementation guidance.
+
+## Goals
+
+- Add one specialized operator agent focused on current agent ecosystems and community-discovered patterns
+- Cover both official and community sources
+- Produce implementation-ready outputs, not just research summaries
+- Require explicit source attribution, dates, freshness, and confidence labels
+- Distinguish credible findings from speculative or risky ones
+
+## Non-Goals
+
+- Building a fully autonomous code execution or scraping system
+- Adding automation infrastructure beyond the prompt-agent definition and repo documentation
+- Treating all community bot or script tactics as safe or endorsed
+
+## Recommended Placement
+
+Place the new file in `specialized/` because the role spans product intelligence, engineering evaluation, and operational synthesis.
+
+Recommended filename:
+
+- `specialized/advanced-agent-intelligence-operator.md`
+
+## Agent Concept
+
+### Name
+
+Advanced Agent Intelligence Operator
+
+### Core Role
+
+An applied research and operations specialist that tracks the newest developments in advanced agents, tools, frameworks, bots, and orchestration patterns, then converts those findings into ranked recommendations and reproducible build kits.
+
+### Distinguishing Behavior
+
+- prioritizes recency and exact dates
+- prefers primary sources and corroborated evidence
+- separates `verified`, `experimental`, and `high-risk` findings
+- turns research into prompts, system specs, workflows, and script blueprints
+- stays opinionated about what is actually worth using now
+
+## Research Scope
+
+The agent should monitor two source lanes:
+
+### 1. Official and mainstream AI ecosystem signals
+
+- official model and platform announcements
+- API and framework releases
+- provider documentation and changelogs
+- research papers and benchmark discussions
+- major GitHub repositories and release notes
+
+### 2. Community-discovered bot and script patterns
+
+- GitHub repos and issue discussions
+- forum and community posts
+- social channels with agent and automation experimentation
+- workflow examples shared by builders
+- emerging bot/script combinations that appear to outperform older approaches
+
+## Workflow
+
+The agent should follow a fixed workflow:
+
+1. Scan current sources across official, research, repo, and community channels
+2. Filter weak, stale, low-signal, or purely hype-driven items
+3. Score findings for recency, capability lift, reproducibility, tool maturity, and risk
+4. Synthesize by category such as frameworks, orchestration, memory, coding agents, browser/computer-use agents, and bots/scripts
+5. Operationalize findings into build kits, prompts, workflows, and script blueprints
+6. Report with exact dates, links, freshness markers, and confidence labels
+
+## Output Package
+
+Each run should aim to return:
+
+- an intelligence brief with exact dates and linked sources
+- ranked recommendations for the strongest current approaches by use case
+- a build kit including system prompt draft, tool stack, orchestration pattern, memory plan, and script/workflow blueprint
+- risk notes covering safety, legality, reliability, abuse potential, and maintenance burden
+- a freshness marker stating what was checked and when
+
+## Guardrails
+
+Because the user wants both legitimate AI ecosystem research and grey-area bot/script intelligence, the agent must include explicit guardrails:
+
+- label findings as `verified`, `experimental`, or `high-risk`
+- distinguish primary-source evidence from community chatter
+- avoid treating unsafe or abusive automation as default recommendations
+- prioritize reproducible techniques over viral but unverified claims
+- call out operational, compliance, and security concerns when relevant
+
+## Repo Changes
+
+### Required
+
+- add new specialized agent file
+- add roster entry in `README.md`
+
+### Optional but not required now
+
+- add usage example in `examples/`
+- add integration notes if the agent proves broadly useful across tools
+
+## Acceptance Criteria
+
+- A new specialized agent exists with identity, mission, workflow, outputs, guardrails, and success metrics
+- The README roster includes the new agent with clear positioning
+- The new agent clearly differs from existing trend, AI engineering, and orchestration agents
+- The prompt emphasizes current-source verification and dated reporting
+
+## Notes
+
+This design intentionally chooses an operator model with guardrails instead of a research-only agent. That keeps the agent aligned with the user goal: finding what currently works best for advanced agents and turning it into something reusable.

docs/plans/2026-03-23-advanced-agent-intelligence-operator.md

@@ -0,0 +1,159 @@
+# Advanced Agent Intelligence Operator Implementation Plan
+
+> **For Claude:** REQUIRED SUB-SKILL: Use superpowers:executing-plans to implement this plan task-by-task.
+
+**Goal:** Add a new specialized agent that researches current advanced-agent trends and operationalizes them into reproducible build guidance, then expose it in the README roster.
+
+**Architecture:** This change is content-driven. The implementation adds one new markdown agent definition in `specialized/` and updates the root `README.md` so the new agent appears in the Specialized Division roster. Verification relies on targeted content checks plus any existing repo validation scripts that apply to agent-file structure.
+
+**Tech Stack:** Markdown, repository conventions in `CONTRIBUTING.md`, existing agent prompt patterns
+
+---
+
+### Task 1: Add the design-approved specialized agent file
+
+**Files:**
+- Create: `specialized/advanced-agent-intelligence-operator.md`
+- Reference: `CONTRIBUTING.md`
+- Reference: `specialized/agents-orchestrator.md`
+- Reference: `product/product-trend-researcher.md`
+
+**Step 1: Write the failing test**
+
+Use a file-existence/content check that should fail before the file exists.
+
+```powershell
+Test-Path 'specialized\advanced-agent-intelligence-operator.md'
+```
+
+**Step 2: Run test to verify it fails**
+
+Run: `Test-Path 'specialized\advanced-agent-intelligence-operator.md'`
+Expected: `False`
+
+**Step 3: Write minimal implementation**
+
+Create `specialized/advanced-agent-intelligence-operator.md` with:
+
+- frontmatter (`name`, `description`, `color`)
+- identity and mission
+- research lanes
+- source-quality and freshness rules
+- workflow
+- output package
+- communication style
+- success metrics
+- guardrails for risky bot/script patterns
+
+**Step 4: Run test to verify it passes**
+
+Run: `Test-Path 'specialized\advanced-agent-intelligence-operator.md'`
+Expected: `True`
+
+**Step 5: Commit**
+
+```bash
+git add specialized/advanced-agent-intelligence-operator.md
+git commit -m "Add advanced agent intelligence operator"
+```
+
+### Task 2: Add the new agent to the README roster
+
+**Files:**
+- Modify: `README.md`
+- Reference: `specialized/advanced-agent-intelligence-operator.md`
+
+**Step 1: Write the failing test**
+
+Check that the README does not yet mention the new agent.
+
+```powershell
+Select-String -Path 'README.md' -Pattern 'Advanced Agent Intelligence Operator'
+```
+
+**Step 2: Run test to verify it fails**
+
+Run: `Select-String -Path 'README.md' -Pattern 'Advanced Agent Intelligence Operator'`
+Expected: no matches
+
+**Step 3: Write minimal implementation**
+
+Add a Specialized Division roster row with:
+
+- linked agent name
+- concise specialty description
+- clear “when to use” guidance
+
+**Step 4: Run test to verify it passes**
+
+Run: `Select-String -Path 'README.md' -Pattern 'Advanced Agent Intelligence Operator'`
+Expected: one or more matches
+
+**Step 5: Commit**
+
+```bash
+git add README.md
+git commit -m "Document advanced agent intelligence operator"
+```
+
+### Task 3: Verify repo-facing outputs
+
+**Files:**
+- Test: `specialized/advanced-agent-intelligence-operator.md`
+- Test: `README.md`
+
+**Step 1: Write the failing test**
+
+Use a structural/content validation command that would reveal missing required sections.
+
+```powershell
+Select-String -Path 'specialized\advanced-agent-intelligence-operator.md' -Pattern '^## '
+```
+
+**Step 2: Run test to verify it fails**
+
+Before implementation, this should produce no output because the file does not exist.
+
+Run: `Select-String -Path 'specialized\advanced-agent-intelligence-operator.md' -Pattern '^## '`
+Expected: file missing or no matches
+
+**Step 3: Write minimal implementation**
+
+Ensure the agent file includes clearly named sections for:
+
+- identity
+- core mission
+- critical rules
+- workflow
+- communication style
+- success metrics
+- advanced capabilities
+
+**Step 4: Run test to verify it passes**
+
+Run:
+
+```powershell
+Select-String -Path 'specialized\advanced-agent-intelligence-operator.md' -Pattern '^## '
+Select-String -Path 'README.md' -Pattern 'advanced-agent-intelligence-operator.md'
+```
+
+Expected:
+
+- multiple `##` section matches in the new agent file
+- one README match linking to the new agent file
+
+**Step 5: Commit**
+
+```bash
+git add specialized/advanced-agent-intelligence-operator.md README.md
+git commit -m "Verify advanced agent intelligence operator content"
+```
+
+Plan complete and saved to `docs/plans/2026-03-23-advanced-agent-intelligence-operator.md`. Two execution options:
+
+**1. Subagent-Driven (this session)** - I dispatch fresh subagent per task, review between tasks, fast iteration
+
+**2. Parallel Session (separate)** - Open new session with executing-plans, batch execution with checkpoints
+
+Which approach?