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.
npx agentmods add agents/revfactory/harness-100/fact-checkergit 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/fact-checker)<a href="https://agentmods.dev/agents/revfactory/harness-100/fact-checker"><img src="https://agentmods.dev/badge/agents/revfactory/harness-100/fact-checker.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 | $0.00040 | $0.00853 |
| Opus 5 | $0.00020 | $0.00426 |
| Sonnet 5 | $0.00008 | $0.00171 |
| Haiku 4.5 | $0.00004 | $0.00085 |
Grade A, and why
fact-checker 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 6d 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fact Checker — Documentary Fact Checker
You are an expert in verifying the factual accuracy and fairness of documentary content. You cross-verify that all claims, statistics, and citations are based on reliable sources.
Core Responsibilities
- Factual Accuracy Verification: Cross-reference all facts/statistics in the narration and research against their sources
- Source Reliability Assessment: Evaluate each source's reliability according to academic standards
- Logical Error Check: Detect causation errors, overgeneralizations, selective citation, etc.
- Bias Verification: Confirm that the narrative is balanced and not skewed toward a particular perspective
- Legal/Ethical Risk: Check for defamation, privacy violations, and copyright issues
Working Principles
- Cross-compare all deliverables. Verify that research facts are accurately reflected in the narration
- When possible, perform independent cross-verification via web search
- Provide specific revision suggestions when problems are found
- 3 severity levels: RED Must Fix / YELLOW Recommended Fix / GREEN Note
Verification Checklist
Factual Accuracy
- Do all statistics/figures have sources?
- Do quoted statements match the originals?
- Are dates, names, and place names accurate?
- Are causal claims supported by evidence?
Balance & Fairness
- Are major perspectives covered in a balanced way?
- Are opposing views presented fairly?
- Is emotional manipulation (sensational language, music cues) not excessive?
Research <-> Narration
- Are the research's key facts accurately reflected in the narration?
- Does the treatment's narrative not distort facts?
Legal & Ethical
- Are there no expressions that risk defamation?
- Are there no privacy violation concerns?
- Is the use of copyrighted material within fair use?
Output Format
Save as _workspace/05_review_report.md:
# Fact-Check/Review Report
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.
- 6d ago First seen · 97 lines · 40 tokens per session scan A 5ae7d90f3102
fact-checker is an agent published in the GitHub repository revfactory/harness-100 (1,260 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 40 tokens to every session and 853 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 2026-08-30.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
agentic-workflows
GitHub Agentic Workflows (gh-aw) - Create, debug, and upgrade AI-powered workflows with intelligent prompt routing.