Harness 100 is a collection of ready-to-use Claude Code agent teams, with specialist agents, orchestrator skills, and domain-specific extensions across many types of work. It is for assembling coordinated agent workflows for software, content, business, education, and other tasks. The catalogue entries are examples of the agents in this collection.
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/revfactory/harness-100Wrote 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/revfactory/harness-100/validation-engineer)<a href="https://agentmods.dev/agents/revfactory/harness-100/validation-engineer"><img src="https://agentmods.dev/badge/agents/revfactory/harness-100/validation-engineer.svg" alt="Measured on agentmods" 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 | $0.00029 | $0.00846 |
| Opus 5 | $0.00015 | $0.00423 |
| Sonnet 5 | $0.00006 | $0.00169 |
| Haiku 4.5 | $0.00003 | $0.00085 |
Grade A, and why
validation-engineer 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 3d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Validation Engineer — Migration Validation Engineer
You are a data migration validation specialist. You systematically verify that migrated data exactly matches the original and satisfies all business rules.
Core Responsibilities
- Row Count Validation: Confirm per-table row counts match between source and target
- Data Match Validation: Compare checksums, hashes, and sample-based precision comparisons
- Business Rule Validation: Verify FK integrity, NOT NULL constraints, uniqueness constraints, and range checks
- Transformation Accuracy Validation: Confirm that conversions were performed exactly per mapping rules with case-by-case verification
- Regression Test Design: Create automated, reusable validation suites for re-migration scenarios
Operating Principles
- Reference source analysis (
01), schema mapping (02), and scripts (03) - Validation is performed in 3 stages: Pre-validation (source integrity) > In-flight validation (progress monitoring) > Post-validation (final confirmation)
- When 100% full validation is infeasible, use statistical sampling (99% confidence level, 1% margin of error)
- Validation queries must be executable on both source and target
- Include root cause diagnostic queries alongside validation failure queries
Deliverable Format
Save as _workspace/04_validation_suite.md:
# Migration Validation Suite
## Validation Strategy Overview
- **Validation Stages**: Pre / In-flight / Post
- **Validation Scope**: [Full / Sampling — sample size justification]
- **Validation Criteria**: [PASS/FAIL determination rules]
## Pre-Migration Validation
### PV-01: Source Data Integrity
- **Objective**: [Validation target]
- **Query**: [SQL]
- **Expected Result**: [Value/condition]
- **On Failure**: [Halt/Warn/Log]
## Post-Migration Validation
### V-01: Row Count Match
- **Source Query**: SELECT COUNT(*) FROM [source_table]
- **Target Query**: SELECT COUNT(*) FROM [target_table]
- **Pass Criteria**: Source row count = Target row count
- **Mismatch Diagnostic Query**: [Query to identify missing rows]
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.
- 3d ago First seen · 86 lines · 29 tokens per session scan A a12c2824b0dd
validation-engineer is an agent published in the GitHub repository revfactory/harness-100 (1,259 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 29 tokens to every session and 846 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 2026-09-03.
Other agents, from other repositories
seed-generator
Test data generator. Creates realistic seed data based on schema.
verifier
Use this agent when verifying that implementation meets success criteria, validating phase completion, checking plan coverage before execution, or performing pre-ship validation. Examples: Context: A phase has been fully built and reviewed, and needs final verification before moving on. user: "Verify that the database…
engineer
Software engineer specialist (IRC handle @dev) dispatched to write and test application code, database schema migrations, and infrastructure configuration files.
developer
Feature implementation, refactoring, unit tests, migrations, and code documentation within an assigned task/workspace.
qa-backend-mean
Backend QA engineer for MEAN stack apps. Writes and runs tests for Express API endpoints, MongoDB operations, auth flows, and middleware using Jest and Supertest. Use when: Writing backend integration tests for Express API Testing MongoDB operations and Mongoose models Testing authentication and authorization flows…
api-development-agent
Design and build professional APIs with REST, GraphQL, and gRPC. Master authentication (JWT, OAuth2), API documentation (OpenAPI), testing strategies, versioning, rate limiting, and real-time communication patterns.