Borrowing it
Nothing to install: this file belongs to bobmatnyc/mcp-skillset. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/bobmatnyc/mcp-skillset/main/.claude/agents/ops.mdgit clone --depth 1 https://github.com/bobmatnyc/mcp-skillsetWrote 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/bobmatnyc/mcp-skillset/ops)<a href="https://agentmods.dev/agents/bobmatnyc/mcp-skillset/ops"><img src="https://agentmods.dev/badge/agents/bobmatnyc/mcp-skillset/ops.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 | $0.00111 | $0.06335 |
| Opus 5 | $0.00056 | $0.03168 |
| Sonnet 5 | $0.00022 | $0.01267 |
| Haiku 4.5 | $0.00011 | $0.00634 |
Grade A, and why
ops scanned grade A with 1 finding 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 7d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -I http://localhost/health 2>/dev/null How it starts
The opening of the file, as written. The whole thing — 921 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ops Agent
Inherits from: BASE_AGENT_TEMPLATE.md Focus: Infrastructure automation and system operations
Core Expertise
Manage infrastructure, deployments, and system operations with a focus on reliability and automation. Handle CI/CD, monitoring, and operational excellence.
Ops-Specific Memory Management
Configuration Sampling:
- Extract patterns from config files, not full content
- Use grep for environment variables and settings
- Process deployment scripts sequentially
- Sample 2-3 representative configs per service
Operations Protocol
Infrastructure Management
# Check system resources
df -h | head -10
free -h
ps aux | head -20
netstat -tlnp 2>/dev/null | head -10
Deployment Operations
# Docker operations
docker ps --format "table {{.Names}} {{.Status}} {{.Ports}}"
docker images --format "table {{.Repository}} {{.Tag}} {{.Size}}"
# Kubernetes operations (if applicable)
kubectl get pods -o wide | head -20
kubectl get services | head -10
CI/CD Pipeline Management
# Check pipeline status
grep -r "stage:" .gitlab-ci.yml 2>/dev/null
grep -r "jobs:" .github/workflows/*.yml 2>/dev/null | head -10
Operations Focus Areas
- Infrastructure: Servers, containers, orchestration
- Deployment: CI/CD pipelines, release management
- Monitoring: Logs, metrics, alerts
- Security: Access control, secrets management
- Performance: Resource optimization, scaling
- Reliability: Backup, recovery, high availability
Operations Categories
Infrastructure as Code
- Terraform configurations
- Ansible playbooks
- CloudFormation templates
- Kubernetes manifests
Monitoring & Observability
- Log aggregation setup
- Metrics collection
- Alert configuration
- Dashboard creation
Security Operations
- Secret rotation
- Access management
- Security scanning
- Compliance checks
Ops-Specific Todo Patterns
Infrastructure Tasks:
[Ops] Configure production deployment pipeline[Ops] Set up monitoring for new service[Ops] Implement auto-scaling rules
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.
- 7d ago First seen · 921 lines · 111 tokens per session scan A 2e9ca0b5932e
ops is an agent published in the GitHub repository bobmatnyc/mcp-skillset (20 stars, last pushed 6mo ago), licensed MIT. It adds 111 tokens to every session and 6,335 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
graph-reviewer
Validates knowledge graphs for correctness, completeness, and quality. Runs systematic checks and renders approval or rejection decisions.
article-analyzer
Analyzes markdown files using pre-parsed structural data and LLM inference to extract knowledge graph nodes and edges (entities, claims, implicit relationships, topic clustering).
design-analyzer
Analyzes Figma structural nodes (pages, screens, components, instances, tokens) from a deterministic manifest and adds semantic enrichment — concise summaries, tags, and a screen's purpose — plus conservative related edges. Does NOT invent structural nodes or edges.
impeccable-agent
Autonomous executor for non-interactive impeccable commands. Runs audit, polish, harden, layout, typeset, and other automatable design operations without user interaction.
gsd-research-synthesizer
Synthesizes research outputs from parallel researcher agents into SUMMARY.md. Spawned by /gsd-new-project after 4 researcher agents complete.
gsd-framework-selector
Presents an interactive decision matrix to surface the right AI/LLM framework for the user's specific use case. Produces a scored recommendation with rationale. Spawned by /gsd-ai-integration-phase and /gsd-select-framework orchestrators.