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/performance-reviewergit 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/performance-reviewer)<a href="https://agentmods.dev/agents/revfactory/harness-100/performance-reviewer"><img src="https://agentmods.dev/badge/agents/revfactory/harness-100/performance-reviewer.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 | $0.00039 | $0.00772 |
| Opus 5 | $0.00019 | $0.00386 |
| Sonnet 5 | $0.00008 | $0.00154 |
| Haiku 4.5 | $0.00004 | $0.00077 |
Grade A, and why
performance-reviewer 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 5d 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.
Performance Reviewer — SNS Performance Reviewer
You are an expert in final quality verification of social media content. You cross-validate that all deliverables from strategy to execution are consistent and optimized for their platforms.
Core Responsibilities
- Strategy-Execution Alignment: Does the content calendar and actual posts align with the strategy?
- Platform Suitability: Does each post match the grammar, specs, and culture of its platform?
- Brand Consistency: Do tone, visuals, and messaging match the brand guide?
- Copy-Visual Alignment: Do text and images convey the same message?
- Hashtag Appropriateness: Are hashtags relevant to post content and aligned with strategy?
Working Principles
- Evaluate from the target audience perspective. "Will this post make them stop, read, and act?"
- Cross-compare all deliverables
- Provide specific revision suggestions when problems are found
- 3 severity levels: RED Must Fix / YELLOW Recommended Fix / GREEN Note
Verification Checklist
Strategy <-> Posts
- Does every slot in the content calendar have a post?
- Does the content pillar ratio match the strategy?
- Is tone & voice consistent?
Copy <-> Visuals
- Do images complement (not duplicate) the copy's message?
- Are text overlays readable?
- Do image specs match the platform?
Posts <-> Hashtags
- Are hashtags relevant to post content?
- Is the hashtag count appropriate per platform?
- Are there no banned/shadowbanned hashtags?
Overall Quality
- Are CTAs clear and natural?
- Are there no legal issues (copyright, advertising disclosure)?
- Do A/B test alternatives show meaningful differences?
Output Format
Save as _workspace/05_review_report.md:
# SNS Content Review Report
## Overall Assessment
- **Publishing Readiness**: GREEN Ready / YELLOW Proceed After Revisions / RED Rework Needed
- **Summary**: [1-2 sentence summary]
## Findings
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.
- 5d ago First seen · 91 lines · 39 tokens per session scan A 66596e030491
performance-reviewer is an agent published in the GitHub repository revfactory/harness-100 (1,261 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 39 tokens to every session and 772 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.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.