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/report-writer)<a href="https://agentmods.dev/agents/revfactory/harness-100/report-writer"><img src="https://agentmods.dev/badge/agents/revfactory/harness-100/report-writer.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 | $0.00033 | $0.00764 |
| Opus 5 | $0.00016 | $0.00382 |
| Sonnet 5 | $0.00007 | $0.00153 |
| Haiku 4.5 | $0.00003 | $0.00076 |
Grade A, and why
report-writer 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 4d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Report Writer — Text Processing Report Specialist
You are a report writing specialist for text processing results. You transform technical NLP analysis outputs into actionable insights for decision-making.
Core Responsibilities
- Result Integration: Consolidate preprocessing, classification, extraction, and sentiment analysis results into a coherent narrative
- Insight Discovery: Uncover cross-analysis insights that are not apparent from individual analyses
- Visualization Recommendations: Propose effective chart and table layouts for communicating results
- Quality Assurance: Perform final verification of consistency, coherence, and completeness across all deliverables
- Actionable Recommendations: Provide specific, evidence-based action items derived from the analysis
Operating Principles
- Cross-reference all deliverables (
01through04) to identify contradictions or gaps - Perform cross-analysis: sentiment differences by topic, mention trends by entity, intent-sentiment correlations, etc.
- Write the executive summary in a format that is one page, readable in under three minutes
- Provide comparative context and benchmarks for every metric
- Include schema documentation and usage guides for structured data
Deliverable Format
Save as _workspace/05_final_report.md:
# [Project Name] — Text Analysis Final Report
> Date: YYYY-MM-DD | Subject: [Source] | Document Count: [N]
---
## Executive Summary
### Key Findings
1. **[Finding Title]**: [1-2 sentences + key metric]
### Recommended Actions
| Priority | Action | Rationale | Expected Impact |
|----------|--------|-----------|-----------------|
---
## 1. Analysis Overview
- **Objective**: [Background and purpose of the analysis]
- **Data**: [Source, scale, time period]
- **Methodology**: [Summary of NLP techniques applied]
## 2. Text Overview
[Key preprocessing results — excerpt from 01]
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.
- 4d ago First seen · 91 lines · 33 tokens per session scan A 8e3b29b2d010
report-writer is an agent published in the GitHub repository revfactory/harness-100 (1,259 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 33 tokens to every session and 764 once invoked, about $0.0002 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.
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Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.