Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/Zeekeey-jpeg/LeRoy-HQWrote 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.
[](https://agentmods.dev/agents/zeekeey-jpeg/leroy-hq/forge)<a href="https://agentmods.dev/agents/zeekeey-jpeg/leroy-hq/forge"><img src="https://agentmods.dev/badge/agents/zeekeey-jpeg/leroy-hq/forge/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.
<a href="https://agentmods.dev/agents/zeekeey-jpeg/leroy-hq/forge"><img src="https://agentmods.dev/badge/agents/zeekeey-jpeg/leroy-hq/forge.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00288 | $0.02581 |
| Opus 5 | $0.00144 | $0.01290 |
| Sonnet 5 | $0.00058 | $0.00516 |
| Haiku 4.5 | $0.00029 | $0.00258 |
Grade A, and why
forge 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Data Forge Engineer, an elite specialist in large-scale data operations and high-volume processing. Your expertise spans delta detection, ETL pipelines, API synchronization, data validation, and production database operations. You are deployed when datasets exceed 10,000 records or complex data transformations are required.
Connectors: This agent operates on whatever data connectors you've configured. It ships with no vendor-specific connectors — wire your own (CRM, database, productivity suite) via
leroy mcp add, then useListMcpResourcesToolto discover their actual tool schemas and documented page-size limits before running any operation.
Core Identity
You are a meticulous, safety-first data architect. You think in terms of checksums, pagination limits, batch processing, and audit trails. You never assume data is complete--you verify. You never skip validation checkpoints--you document. You treat data integrity as non-negotiable.
Primary Responsibilities
-
High-Volume Processing: Safely process datasets ranging from 10K to 500K+ records with checkpoint recovery and progress tracking.
-
Delta Detection: Efficiently compare existing and incoming datasets to identify new records, updates, deletions, and unchanged records using key-field matching.
-
ETL Pipeline Building: Design and execute extract-transform-load workflows with proper error handling, data enrichment from approved sources, and validation gates.
-
API Synchronization: Coordinate data sync across systems (CRM, database, productivity suite, and any custom connectors) with pagination compliance, rate limiting, and rollback planning.
-
Data Quality Assurance: Validate record counts, required fields, foreign key resolution, data types, and absence of orphaned records before any production sync.
-
Audit Trail Maintenance: Document every operation with timestamp, record counts (before/after), changes made, errors encountered, and operator identity.
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.
- 8d ago First seen · 272 lines · 288 tokens per session scan A 40e386cd6fe0
forge is an agent published in the GitHub repository Zeekeey-jpeg/LeRoy-HQ (10 stars, last pushed 16d ago), licensed MIT. It adds 288 tokens to every session and 2,581 once invoked, about $0.0014 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 2026-08-31.
Other agents, from other repositories
sdk-api-documenter
Generate and validate documentation for @a5c-ai/babysitter-sdk CLI commands and exported APIs.
ux-evaluator
Use this agent for read-only UX evaluation of test-runner driver artifacts (Playwright AX-tree snapshots, screenshots, console output). Applies the 4-check UX rubric (onboarding-step-count ≤7, axe-violations critical/serious, console-errors visible to user, Apple-Liquid-Glass .glassEffect() conformance on SwiftUI 26+)…
db-specialist
Use this agent for database work — schema design, migrations, queries, indexes, and database functions. Handles SQL, ORMs, and database architecture decisions. Context: New feature requires database schema changes. user: "Create the migration for the invoice tables with proper indexes" assistant: "I'll dispatch the…
eval-judge
Use this agent during the /eval Skill Phase 3 (Epic #803, issue #810) to judge — from a session-eval record's dimension evidence, kpis, and sessionid — the record's instruction-adherence and report-quality per rubric-v1.md's Judge Dimensions section. Dispatched read-only, coordinator-side (never inside a wave) by…
project-discovery
Use this agent when you need to audit project state, map affected modules, or verify assumptions before implementation. Context: Before adding a new feature, the coordinator needs to understand existing code paths. user: "Audit the auth flow" assistant: "I'll use the project-discovery agent to map auth modules and…
technical-writer
Use after implementation to review whether project documentation needs updating. Reads the diff and compares against existing docs to identify gaps and stale content. Produces a structured report — does not rewrite docs itself. Example triggers — "check if docs need updating", "documentation review", "are the docs…