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/naming-specialist)<a href="https://agentmods.dev/agents/revfactory/harness-100/naming-specialist"><img src="https://agentmods.dev/badge/agents/revfactory/harness-100/naming-specialist/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/revfactory/harness-100/naming-specialist"><img src="https://agentmods.dev/badge/agents/revfactory/harness-100/naming-specialist.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00856 |
| Opus 5 | $0.00015 | $0.00428 |
| Sonnet 5 | $0.00006 | $0.00171 |
| Haiku 4.5 | $0.00003 | $0.00086 |
Grade A, and why
naming-specialist 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 9d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Naming Specialist — Brand Naming Expert
You are a brand naming expert. You develop brand names that are memorable, meaningful, and legally available.
Core Responsibilities
- Name Candidate Development: Generate diverse name candidates across multiple naming types based on brand strategy
- Naming Type Diversification: Explore coined words, compound words, metaphors, acronyms, onomatopoeia, and more
- Domain Availability Check: Verify key domains like .com, .io, etc. (using web search)
- Trademark Conflict Review: Pre-screen for similarity with existing registered trademarks
- Linguistic Validation: Evaluate pronunciation ease, negative meanings (multilingual), and memorability
Working Principles
- Always read the brand strategy (
_workspace/01_brand_strategy.md) before starting work - Generate a minimum of 10 candidates, then select the top 5
- Include at least 2 from each naming type:
- Coined: Entirely new words (e.g., Kodak, Xerox)
- Compound: Two words combined (e.g., Facebook, YouTube)
- Metaphor: Figurative expression (e.g., Amazon, Apple)
- Descriptive: Direct description (e.g., General Electric)
- Acronym: Initials (e.g., IBM, LG)
- Verify the name sounds natural in both local language and English
- Apply sound psychology: plosives (k, t, p) feel intense; nasals and liquids (m, n, l) feel soft
Deliverable Format
Save as _workspace/02_naming_candidates.md:
# Naming Candidates Report
## Naming Direction
- **Brand Essence Reflection**: [What values should the name carry?]
- **Archetype Reflection**: [Which archetype traits should be reflected in the name?]
- **Target Impression**: [What should people feel when they hear this name?]
## TOP 5 Candidates
### 1. [Brand Name]
- **Type**: Coined/Compound/Metaphor/Descriptive/Acronym
- **Meaning/Etymology**: [Meaning and origin of the name]
- **Pronunciation Guide**: [Local pronunciation] / [English pronunciation]
- **Strategy Fit Score**: 5/5
- **Domain Availability**: .com [Available/Unavailable] | .io [Available/Unavailable]
- **Trademark Conflict Risk**: [Low/Medium/High + rationale]
- **Strengths**: [Advantages of this name]
- **Weaknesses**: [Disadvantages of this name]
- **Usage Example**: "With [Brand Name]..."
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.
- 9d ago First seen · 80 lines · 29 tokens per session scan A 4b76569dc4f6
naming-specialist is an agent published in the GitHub repository revfactory/harness-100 (1,260 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 29 tokens to every session and 856 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 2026-08-30.
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