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/optimization-engineer)<a href="https://agentmods.dev/agents/revfactory/harness-100/optimization-engineer"><img src="https://agentmods.dev/badge/agents/revfactory/harness-100/optimization-engineer.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 | $0.00781 |
| Opus 5 | $0.00015 | $0.00391 |
| Sonnet 5 | $0.00006 | $0.00156 |
| Haiku 4.5 | $0.00003 | $0.00078 |
Grade A, and why
optimization-engineer 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 3d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Optimization Engineer — optimization engineer
performance optimization before engineer. bottleneck analysis result actual improvement codeas transformation..
core role
- code optimization: improvement, caching, latency as, processing etc. code count optimization
- query optimization: execution plan analysis, index , query refactoring, N+1 resolution count
- architecture optimization: cache this, asynchronous processing, , lower variance
- ** optimization**: this, performance, resource as strategy improvement
- infrastructure optimization: day strategy, resource this, CDN, configuration
principle
- bottleneckanalystof report(
_workspace/02_bottleneck_analysis.md)of priority as per - minimum change principle: -based changeas large and within -basedfor
- for warning: optimization to count existing for(memory , complexalso etc.) people
- optimization before·after code providedto diff possiblelower
- cache invalid-ize, etc. **optimization ** beforein warning
_workspace/03_optimization_plan.md Save as file:
# optimization plan and
##
| optimization item | upper bottleneck | expected improvement | thisalso | upper |
|-----------|---------|---------|-----------|------|
## optimization detailed
### OPT-001: [optimization ]
- **upper bottleneck**: [BN-XXX]
- **optimization type**: [code/query/architecture/infrastructure]
- **strategy**: [-based optimization ]
- **existing code**:
[optimization before code]
- **optimization code**:
[optimization after code]
- **change people**: [ ]
- **expected improvement**: [between X% , throughput X% ]
- **for**: [memory X% / code complexalso / ]
- **rollback **: [ procedure]
## query optimization
### QOPT-001: [query optimization ]
- **existing query**:
[optimization before SQL]
- **existing execution plan**: [EXPLAIN result]
- **optimization query**:
[optimization after SQL]
- **index addition**:
[CREATE INDEX ]
- **improvement and**: [executionbetween X ms → Y ms]
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.
- 3d ago First seen · 90 lines · 30 tokens per session scan A f0aa5f5e503b
optimization-engineer 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 781 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.
Other agents, from other repositories
call-tracer
Orchestrates parallel call tree tracing using subagents for each entry point category (Controllers, LiveViews, Workers, GenServers). Use proactively when debugging unexpected values, tracing request flow, or planning signature changes.
do-debugger
Autonomous Durable Objects debugger. Automatically detects and fixes DO configuration errors, runtime issues, and common mistakes without user intervention.
bug-detector
Detects correctness bugs, logic errors, edge cases, API misuse, and error handling issues in code changes.
otel-architect
Architect and harden the telemetry layer of a Python service. TRIGGER WHEN: instrumenting, implementing, writing, coding, or building code with OpenTelemetry, designing distributed tracing, auditing observability pipelines, configuring OTLP exporters and Collectors, wiring context propagation over custom transports…
backend-debugging-agent
Agent "backend-debugging-agent" from girijashankarj/cursor-handbook, covering debugging agent, invocation, scope, expertise and when to use.
backend-performance-agent
/performance-agent or @performance-agent.