DevOps & Infra

markfulton Skill

Runs once by hand on the first day and once a month after that, on the first weekday, light browser lane. On the first run it researches the business from its own public surfaces before asking anything, writes the strategy folder, seeds the pipeline, reconciles the schedule table, and registers the recurring jobs. On every monthly run it re-reads the evidence the kit produced, applies what changed to the files it owns, and carries every member written setting across verbatim. It holds every outbound action unless you released the channel, and it never enters a credential.

markfulton Skill

Weekdays, file work only, no browser at all. Reads every ledger, queue file, and run record written since its own cursors, turns the member's ticks into sent rows and closed cards, folds the card inbox, re-renders the pipeline board, and writes the short morning brief the member opens first. It names the veto window every day. It holds every outbound action unless you released the channel, and it never touches a credential.

markfulton Skill

Weekly, on a Friday, read only everywhere. Scores the week from the ledgers with a source path beside every number, replays the browser flows the other routines depend on, names one thing to kill and one thing to scale, and files both as cards. It sends only where you released the channel, spends only where you released it, never touches a credential, and never writes a number it did not count out of a named file this run.

octagonai Bundle

Extract product development and pipeline updates from earnings calls, including clinical trial progress, regulatory submissions, and launch timelines.

h4vzz Skill

Set up a continuous integration and continuous delivery (CI/CD) pipeline for a software project, automating builds, tests, and deployments across environments.

h4vzz Skill

Deploy trained machine learning models as production-ready services using REST APIs, containers, serverless functions, and orchestration platforms.

h4vzz Skill

A skill to create, manage, and automate machine learning pipelines.

h4vzz Skill

Monitor cloud infrastructure and applications using metrics, logs, and traces to provide real-time observability into performance, health, and reliability.

h4vzz Skill

Set up and orchestrate multi-container Docker applications using docker-compose, including service configuration, networking, volumes, and environment management.

ske-labs Skill

Calculate and test correctly shifted Ichimoku components. Use when evaluating price/cloud, TK-cross, Chikou, and cloud-state features without future leakage or confirmation-count scoring.

internscience Skill

Run GoCa coarse-grained protein MD pipeline and collect key simulation artifacts from a unified run directory.

internscience Skill

Unified EquiScore skill for pocket extraction, pocket scoring, and end-to-end docking-to-score pipeline execution.

encod3d-sec Skill

RCE hunting - template injection, YAML/XML deserialization, dependency confusion, Kubernetes surfaces, CVE-specific exploits (Apache CVE-2021-41773, Spring CVE-2022-22963). OOB-mandatory for blind cases. Wiki-first, FIND schema output.

encod3d-sec Skill

CI/CD pipeline attack hunting (GitHub Actions focus) - pwn requests (pull_request_target), script injection, self-hosted runner takeover, cache poisoning, OIDC-to-cloud token theft, poisoned pipeline execution. Wiki-first, FIND schema output.

encod3d-sec Skill

SSRF hunting - OOB-mandatory methodology. Cloud metadata, blind SSRF via Collaborator/interactsh, redirect-based bypass, headless browser chains. Wiki-first, FIND schema output.

encod3d-sec Skill

Post-engagement knowledge harvest AND harness retrospective - after a box/bugbounty/pentest/CTF is completed, first diff how the engagement was EXECUTED against the skills/hooks that governed it (what discipline was skipped) and improve the harness, then sweep the whole engagement for GENERIC reusable knowledge NOT already in wiki/ and land it via the leak-gated stage->promote pipeline. Use at close-out or when asked to "extract learnings", "what did we learn", "harvest lessons into wiki", "distill this engagement", "post-mortem into the wiki", "what did we do wrong", "improve the harness from this box".

encod3d-sec Skill

Exposed-secrets hunting - .git/ dir + history mining, exposed .env/config files, hardcoded keys in JS bundles + source maps, S3/blob exposure, public-repo secret search, CI/CD leakage. Live-validation mandatory. Wiki-first, FIND schema output.

odjaramillo Skill

CI/CD pipeline patterns for automated testing and deployment. Trigger: When configuring CI/CD pipelines.

odjaramillo Skill

Firebase gives you a complete backend in minutes - auth, database, storage, functions, hosting. But the ease of setup hides real complexity. Security rules are your last line of defense, and they're often wrong. Firestore queries are limited, and you learn this after you've designed your data model. This skill covers Firebase Authentication, Firestore, Realtime Database, Cloud Functions, Cloud Storage, and Firebase Hosting. Key insight: Firebase is optimized for read-heavy, denormalized data. I

odjaramillo Skill

Terraform infrastructure as code patterns and best practices. Trigger: When writing Terraform infrastructure code.

richfrem Bundle

Interactive initialization script that generates Azure AI Foundry Agent API deployment wrappers (Python SDK and Bicep basics) from an existing Agent Skill. Use when adapting a skill into an Azure Foundry environment.

richfrem Bundle

Interactive initialization script that generates a compliant Agent Skill containing pre-flight environment checks, subprocess execution scaffolding, and a security-override config. Use when authoring new workflow routines that depend on external containerized runtimes (e.g., Docker, Nextflow, HPC).

richfrem Bundle

Python dependency and environment management for multi-service or monorepo python backends. Use when: (1) adding, upgrading, or removing a Python package, (2) responding to Dependabot or security vulnerability alerts (GHSA/CVE), (3) creating a new service that needs its own requirements files, (4) debugging pip install failures or Docker build issues related to dependencies, (5) reviewing or auditing the dependency tree, (6) running pip-compile. Enforces the pip-compile locked-file workflow and tiered dependency hierarchy.

richfrem Bundle

Scaffold a traditional deterministic GitHub Actions CI/CD workflow. Use this when creating build, test, deploy, lint, release, or security scan pipelines. This is distinct from agentic workflows — no AI is involved at runtime.

richfrem Bundle

Scaffold GitHub Agent files from an existing Agent Skill. Generates IDE/UI agents (invokable from GitHub Copilot Chat via slash command) and/or CI/CD autonomous agents (GitHub Actions quality gates with Kill Switch). Use when converting a Skill into a GitHub-native agent.

buildpad-ai Skill

Manage AWS Amplify environment variables for the project's main app or a microapp via Buildpad platform MCP tools (amplify_get_env_vars, amplify_set_env_vars). Use when a deployment needs env vars read, set, updated, or removed without opening the Amplify Console.

paulingram Skill

Use at the END of a work session — before compacting context, before declaring work done, or when invoked via /architect-team:closeout. A double-check that reviews the changes made against the requirement and confirms the documentation has been suitably updated; if any doc in the currency inventory is lax or incomplete, it updates it itself rather than just flagging it. Fires automatically before compaction via the PreCompact hook (hooks/precompact-closeout.py), which surfaces the deterministic staleness signals from hooks/closeout_check.py. Reuses the documentation-currency discipline + the doc-updater pattern; operates from the working-tree diff so it works OUTSIDE a full pipeline run.

paulingram Skill

Discover, match, and consume phenotypes — pre-made generalized deployable application architectures (a blueprint + a parameterized scaffold + metadata) that the pipeline proposes reuse-first or is told to use. Use when a request matches a known architecture domain (user management, config management, an AI agent/prompt layer), when the user says "use the X phenotype" or "use phenotypes", or when the architect-team pipeline reaches reuse-first design and a phenotype could seed the work.

paulingram Skill

A persona-driven UX-test orchestrator. Takes a persona description + objectives + target site (URL or `--dev` for the project's dev environment) + credentials (env-var reference, never the secret). Maps the site (fresh or freshness-checked via `intake-and-mapping`), drafts a literal Playwright flow matching the user's request, dispatches 3 `flow-explorer` agents to propose 10-15 additional adjacent flows each, distills to a unique set, authors one `.spec.ts` per flow, dispatches 3 `flow-executor` agents to run every flow in parallel against the live target, resolves verdict disagreements via loop-until-converged convergence (no fixed cycle cap), documents bugs, and auto-routes them through the existing `bug-fix-pipeline` (v0.9.22). The capability is the structural bridge between 'human describes a persona's UX concern' and 'the bug-fix-pipeline has the work queued.' Reached via `/architect-team:ux-test`.

paulingram Bundle

Use when a bug needs to be fixed end-to-end faster than the full architect-team-pipeline can deliver, but with the same rigor where it matters. A sibling orchestrator playbook whose Phases B−1 through B8 mirror the main pipeline's structural points but replace the Phase 2-5 parallel-team-spawn / 6-team-review with a tight replicate → reproduce-test → propose → fix → QA-replay loop. The body documents the five non-negotiable disciplines (replicate first, reproduction IS the regression test, generalized fix not symptom patch, QA replay against the live dev environment, live-dev-by-default with production opt-in). Accepts the same two input forms as the main /architect-team — a requirements folder OR a plain-language requirement typed directly as prose.

paulingram Skill

Use when the architect-team / bug-fix / ux-test pipeline receives free-text prose (not a directory of OpenSpec / Superpowers artifacts), OR when /architect-team:refine-prompt is invoked standalone. Conversationally refines the prompt with codebase-map grounding and multi-axis clarity grading (clarity / scope / acceptance / grounding / conflict / scope-fidelity), iterating with the user until satisfied, then outputs a structured refined-prompt markdown the downstream pipeline consumes. A domain gate, not a process gate — the user-confirmation step IS the deliverable; --no-refine bypasses it. The body documents the R1-R6 phases, the six grading axes, standalone-vs-pipeline mode, and the scope-fidelity domain gate per `common-pipeline-conventions` `## Scope discipline`.

paulingram Skill

A passive observer team that watches when testing is happening and produces a per-run report. Generic across 3 source adapters — local test runs (pytest / playwright / npm test / vitest / jest) / CI runs (GitHub Actions / GitLab CI) / production QA + UAT (APM / log-tail). Strictly log-only — no mid-run interrupts, no auto-SR filing, no pipeline gating.

paulingram Skill

Use when a data-engineering ask should be driven end-to-end as a first-class lane — build the warehouse dbt models, mine the stored procedures into a data dictionary, design the Airflow pipeline — faster than the full architect-team-pipeline but with the same rigor where it matters. A sibling orchestrator playbook (like bug-fix-pipeline) whose phases D−1 through D8 reuse the main pipeline's structural points rather than duplicating them; D0 dispatches data-engineering-exploration verbatim (the lane is its third caller), D2–D6 run Phases 2–6 verbatim (the full evidence stack), and the two new disciplines are the D−1 warm-catalog-first check (query the Run A knowledge server plus its freshness verdict before a rebuild) and the D7 catalog-refresh (rebuild the dictionary, re-index the server, mine to MemPalace, leaving the catalog warm). Accepts the same two input forms as architect-team — a requirements folder OR plain-language prose typed directly.

paulingram Skill

Use when a requirement carries a Claude Design offer — a claude.ai/design/p link and/or a claude_design MCP mention — and you need to import that design project into the pipeline as a front-end oracle. Detects the offer, fetches the WHOLE project natively through the claude_design MCP, materializes it locally path-safely, and hands it to the existing interactive-mockup oracle path. Degrades gracefully with an instruct-then-fallback to the zip/local design-input path when the MCP is unavailable, so a run never dead-ends. The deterministic detector, URL parser, materializer, and fallback planner live in scripts/claude_design/claude_design_import.py; this skill is the contract.

paulingram Skill

Use when the architect-team is invoked against a visual codebase (UI present, requirements absent OR partially specified) and must DERIVE the API design from what the screens reveal — the Phase 0 "review this codebase / design the API for this visual" case. Runs the Exploration Pipeline, a scope-gated 7-stage flow with 3-reviewer convergence per stage (each convergence wrapped in a ralph-loop whose completion-promise is total reviewer agreement) and per-stage checklists that gate the next stage's freeze. The body documents every stage, the checklists, the ralph-loop governance, the openspec-skill conversion, and the original 4-stage flow that remains valid as a strict subset.

paulingram Skill

Use whenever a phase of the architect-team pipeline needs to query prior context or persist a newly-produced artifact to the per-workspace MemPalace store. The orchestrator and named subagents (system-architect, diagnostic-researcher, route-mapper, cartographer-flow callers) consult this skill for the canonical wake-up query at intake, the search patterns each role uses before producing output, the auto-mine rules that fire when an artifact is written (CODEBASE_MAP, ROUTE_MAP, INTEGRATION_MAP, DESIGN_MAP, RCA artifacts, diagnostic plans, solution requirements, handoffs, coverage maps, final reports), and the MCP wire-up that lets every subagent reach the 29 mempalace MCP tools.