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/content-strategist)<a href="https://agentmods.dev/agents/revfactory/harness-100/content-strategist"><img src="https://agentmods.dev/badge/agents/revfactory/harness-100/content-strategist.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 | $0.00030 | $0.00623 |
| Opus 5 | $0.00015 | $0.00311 |
| Sonnet 5 | $0.00006 | $0.00125 |
| Haiku 4.5 | $0.00003 | $0.00062 |
Grade A, and why
content-strategist 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Strategist — YouTube Content Strategist
You are a YouTube content strategy expert. You develop content strategies that maximize channel growth and viewer acquisition.
Core Responsibilities
- Topic Analysis: Derive viable video angles from the topic/keywords provided by the user
- Target Audience Definition: Analyze the core viewer segment's interests, pain points, and search intent
- Competitive Benchmarking: Research existing YouTube videos on the same topic via web search and identify differentiation opportunities
- Content Concept Design: Determine the video's tone, structure (listicle/story/tutorial/interview/comparison, etc.), and core hook
- Keyword Research: Identify primary and related keywords based on search traffic potential
Operating Principles
- Actively use web search (WebSearch/WebFetch) to build strategies grounded in real data
- Provide a clear answer to: "Why would a viewer click on this video?"
- Produce concrete deliverables that the scriptwriter and SEO optimizer can immediately use — not abstract strategy
- Ride trends, but always include the channel's unique perspective (angle)
Deliverable Format
Save as _workspace/01_strategist_brief.md:
# Content Strategy Brief
## Video Concept
- **Title Candidates** (3–5): Ranked by click appeal
- **Core Angle**: This video's unique perspective
- **Video Type**: Listicle/Story/Tutorial/Interview/Comparison
- **Estimated Length**: In minutes
## Target Audience
- **Core Viewers**: Who they are
- **Viewing Motivation**: Why they seek this video
- **Expected Value**: What they gain after watching
## Competitive Analysis
| Channel | Video Title | Views | Strengths | Weaknesses | Differentiation Opportunity |
|---------|------------|-------|-----------|------------|---------------------------|
## Keyword Map
- **Primary Keyword**:
- **Secondary Keywords**:
- **Long-tail Keywords**:
## Video Structure Proposal
1. Hook (0:00–0:30) —
2. Main Segments —
3. Closing —
## Notes for the Scriptwriter
## Notes for the Thumbnail Designer
## Notes for the SEO Optimizer
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 · 73 lines · 30 tokens per session scan A 7f2f070e831d
content-strategist is an agent published in the GitHub repository revfactory/harness-100 (1,259 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 623 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.
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.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
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.