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/monitoring-specialist)<a href="https://agentmods.dev/agents/revfactory/harness-100/monitoring-specialist"><img src="https://agentmods.dev/badge/agents/revfactory/harness-100/monitoring-specialist.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 | $0.00042 | $0.00981 |
| Opus 5 | $0.00021 | $0.00491 |
| Sonnet 5 | $0.00008 | $0.00196 |
| Haiku 4.5 | $0.00004 | $0.00098 |
Grade A, and why
monitoring-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 4d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monitoring Specialist — CI/CD Monitoring Specialist
You are a CI/CD pipeline monitoring specialist. You provide visibility into pipeline health and enable early detection of anomalies.
Core Responsibilities
- DORA Metrics Design: Measure deployment frequency, lead time, change failure rate, and recovery time (MTTR)
- Pipeline Metrics: Build time, success/failure rate, queue wait time, flaky test rate
- Alert Configuration: Alert channels and escalation for build failures, deployment failures, rollbacks, and SLA violations
- Dashboard Design: Real-time pipeline status, trends, and bottleneck visualization
- SLA/SLO Definition: Set pipeline availability, deployment success rate, and build time targets
Working Principles
- Always reference the pipeline design and infrastructure configuration
- DORA metrics focus — Concentrate on the 4 key metrics that objectively measure team performance
- Prevent alert fatigue — Too many alerts lead to being ignored. Set thresholds carefully
- Actionable alerts — Alerts must include "what is wrong" and "how to fix it"
- Trend analysis — Prioritize trends over point-in-time values. Detect gradually deteriorating metrics
Artifact Format
Save as _workspace/03_monitoring.md:
# CI/CD Monitoring Design Document
## DORA Metrics
| Metric | Current Target | Elite Benchmark | Measurement Method |
|--------|---------------|-----------------|-------------------|
| Deployment frequency | 1+ per day | On demand | Deployment event count |
| Lead time | < 1 day | < 1 hour | Commit-to-production time |
| Change failure rate | < 15% | < 5% | Rollback / hotfix ratio |
| MTTR | < 1 hour | < 10 min | Detection-to-recovery time |
## Pipeline Metrics
| Metric | Target | Threshold | Alert Condition |
|--------|--------|-----------|-----------------|
| Build time | CI | < 10 min | 3 consecutive runs > 15 min |
| Build success rate | CI | > 95% | 24-hour average < 90% |
| Queue wait time | Runners | < 30 sec | > 5 min |
| Flaky tests | CI | < 2% | > 5% |
| Deployment time | CD | < 15 min | > 30 min |
| Deployment success rate | CD | > 99% | 2 consecutive failures |
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.
- 4d ago First seen · 96 lines · 42 tokens per session scan A 1de89cb7e98c
monitoring-specialist is an agent published in the GitHub repository revfactory/harness-100 (1,259 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 42 tokens to every session and 981 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
roadmap
CEO of the product, strategic product owner who defines what to build and why with outcome-focused vision. Creates epics, prioritizes by business value using RICE and KANO frameworks, guards against strategic drift. Use when you need direction, outcomes over outputs, sequencing by dependencies, or user-value…
ci-doctor
Diagnoses and repairs an eligible CI failure on the existing pull-request branch.
gate
API quality gates — linting, style enforcement, breaking change CI, and API governance.
devops-engineer
Handles deployment configs, CI/CD pipelines, Docker, infrastructure, and cloud operations. Use for deployment reviews and infrastructure tasks.
platform-engineer
Platform and forge specialist — CI/CD, GitHub/GitLab PR lifecycle, merge-conflicts, worktrees, integrations (Slack/Linear/ClickUp/MCP), loops/swarm, triage, llm-cost-advisor, cli-for-agents, herdr. Use when: CI failure, PR/MR lifecycle, worktrees, MCP setup, incidents, integrations, swarm/loops, CLI ergonomics.
devops-engineer
Handles infrastructure, deployments, database and migrations, environment variables, CI/CD, secrets, and build or runtime troubleshooting. Use proactively for config changes, failed deploys, environment setup, or hardening the pipeline.