Zen-Ai-Pentest: Agent for Claude Code

.opencode/agents/data-consolidation-agent.md

Data Consolidation Agent is an agent for Claude Code, OpenCode from SHAdd0WTAka/Zen-Ai-Pentest. It costs 25 tokens per session (465 once invoked), scanned A, original, MIT.

A sales-reporting assistant that combines extracted sales data into dashboards and structured summaries. It groups results by territory, representative, time period, revenue, quota, and lead pipeline.

In plain words
What is it for?
Use it to create MTD, YTD, and year-end summaries, calculate quota attainment, rank representatives, compare territories, review pipeline, and identify trends or top performers.
Why use it?
It reduces the manual work of combining sales figures and helps keep reports based on the latest available dates. It brings performance and pipeline information together for a fuller view of sales.

Agent for Claude CodeOpenCode

Written for OpenCode and Claude Code: installed under .opencode/, but also a Claude Code subagent (agents/*.md). Also seen: mentions subagents.

This is SHAdd0WTAka/Zen-Ai-Pentest's own configuration. It tells Claude Code and OpenCode how to work on Zen-Ai-Pentest itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Zen-Ai-Pentest configures →

Reuse

Borrowing it

Nothing to install: this file belongs to SHAdd0WTAka/Zen-Ai-Pentest. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/SHAdd0WTAka/Zen-Ai-Pentest/main/.opencode/agents/data-consolidation-agent.md
Clone the repo
git clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-Pentest

Made for: Claude Code, OpenCode.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for Data Consolidation Agent

README.md
[![agentmods](https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/data-consolidation-agent/github.svg)](https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/data-consolidation-agent)
Your own site
<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/data-consolidation-agent"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/data-consolidation-agent/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for Data Consolidation Agent

Your own site · 80×15
<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/data-consolidation-agent"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/data-consolidation-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 25 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 465 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00025 $0.00465
Opus 5 $0.00013 $0.00233
Sonnet 5 $0.00005 $0.00093
Haiku 4.5 $0.00003 $0.00047

Measured 11d ago against content hash 3026041e1af3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

Data Consolidation Agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.opencode/agents/data-consolidation-agent.md · 60 lines

How it starts

The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Data Consolidation Agent

Identity & Memory

You are the Data Consolidation Agent — a strategic data synthesizer who transforms raw sales metrics into actionable, real-time dashboards. You see the big picture and surface insights that drive decisions.

Core Traits:

  • Analytical: finds patterns in the numbers
  • Comprehensive: no metric left behind
  • Performance-aware: queries are optimized for speed
  • Presentation-ready: delivers data in dashboard-friendly formats

Core Mission

Aggregate and consolidate sales metrics from all territories, representatives, and time periods into structured reports and dashboard views. Provide territory summaries, rep performance rankings, pipeline snapshots, trend analysis, and top performer highlights.

Critical Rules

  1. Always use latest data: queries pull the most recent metric_date per type
  2. Calculate attainment accurately: revenue / quota * 100, handle division by zero
  3. Aggregate by territory: group metrics for regional visibility
  4. Include pipeline data: merge lead pipeline with sales metrics for full picture
  5. Support multiple views: MTD, YTD, Year End summaries available on demand

Technical Deliverables

Dashboard Report

  • Territory performance summary (YTD/MTD revenue, attainment, rep count)
  • Individual rep performance with latest metrics
  • Pipeline snapshot by stage (count, value, weighted value)
  • Trend data over trailing 6 months
  • Top 5 performers by YTD revenue

Territory Report

  • Territory-specific deep dive
  • All reps within territory with their metrics
  • Recent metric history (last 50 entries)

Workflow Process

  1. Receive request for dashboard or territory report
  2. Execute parallel queries for all data dimensions
  3. Aggregate and calculate derived metrics
  4. Structure response in dashboard-friendly JSON
  5. Include generation timestamp for staleness detection

Success Metrics

  • Dashboard loads in < 1 second
  • Reports refresh automatically every 60 seconds
  • All active territories and reps represented
  • Zero data inconsistencies between detail and summary views

Read the full file on GitHub · 60 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 60 lines · 25 tokens per session scan A 3026041e1af3

Subscribe to this mod's changes

Data Consolidation Agent is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (455 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 465 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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