个人作者
Stephen J Newhouse
Data Scientist, Bioinformatician, Dad, Husband, MS warrior
- Skills
- 41
- 仓库
- 1
- 职业覆盖
- 5
- 场景覆盖
- 5
- Stars
- ★ 6
Stephen J Newhouse 的 Skills 41
deploy-helper
You can use this to help with deploy stuff, deploying, deployments, releases, shipping, pushing to prod, going live, rollouts.
writing-for-agents
Writing documents for agents. Use when creating or editing skills, or modifying AGENTS.md or CLAUDE.md.
verify-plan
Slash entry for plan verification: runs plan-verification on an existing AA-MA plan, writes [task]-verification.md, and with --iterate loops until the plan converges. Use when the user types /verify-plan or wants the verification report saved.
verify-impl
Post-impl adversarial review symmetric to /verify-plan. Dispatches up to 5 parallel audit agents (code-reviewer, security-auditor, tdd-sequence-auditor, context7-evidence-auditor, future-proofing-auditor) based on the milestone's plan-declared Audit-Profile. CRITICAL findings surface via AskUserQuestion accept/dispute/defer panel before §7.3 user authorization. Introduced in v0.8.0 per ADR-0005. Invoked by Phase 6.8 of /execute-aa-ma-milestone.
understand-codebase
Onboard to a new, inherited, or shared codebase. Read it, understand it, map it, and learn its conventions, versioning, tests, tech stack, rules (AGENTS.md / CLAUDE.md / .cursorrules / etc.), build/run/CI, integrations, security posture, and repo health — then produce an honest pros/cons verdict, a "contribute safely" playbook, and an "add a feature" playbook, written to ONBOARDING.md at the repo root plus a .claude/onboarding/ set of deep-dives — and optionally author an AGENTS.md if one is missing, or review and propose improvements to an existing one. Tiered (Quick / Standard / Deep). Reuses codemem (index + diagrams), gsd-map-codebase, system-mapping, code-intelligence, impact-analysis rather than re-implementing them; Deep tier runs a TeamCreate agent-team. Keywords: new codebase, shared codebase, inherited code, onboard, understand this repo, how do I contribute, how do I add a feature, ramp up, get oriented, ONBOARDING.md, AGENTS.md, codebase walkthrough, joining a project.
token-compression
Output token compression for AA-MA workflows. Reduces response tokens by 40-75% while preserving full technical accuracy. Three intensity levels mapped to execution modes: lite (HITL), full (general), ultra (AFK). Auto-activates during AA-MA execution based on task Mode field. Manual activation via /compress lite|full|ultra.
system-mapping
Lightweight pre-flight checklist for understanding system context before code changes. Perform 5-point analysis of architecture, execution flows, logging, dependencies, and environment. Use before modifying unfamiliar code or multi-file changes.
sole-dev-merge
GitHub PR merge for a sole developer — local fixes and checks, code and security review, push and PR, CI watch, merge and cleanup, through one tested script (sdm.sh). Run only when the user asks to merge a branch or PR.
secrets-management
Implement secure secrets management for CI/CD pipelines using Vault, AWS Secrets Manager, or native platform solutions. Use when handling sensitive credentials, rotating secrets, or securing CI/CD environments.
secops
Security review, dependency audit and scanner choice: routes each artifact to its scanner (Ruff S for Python, gitleaks for secrets, pip-audit for the Python lock, osv-scanner for JS, R and other lockfiles, ShellCheck for shell), names each finding's rule and CWE, and sets the layer each check runs at (edit, commit, CI). Use when reviewing code or a file for security problems (load it before reading the code), auditing dependencies for known vulnerabilities, or choosing a repo's security checks.
retro
Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware: breaks down per-person contributions with praise and growth areas.
python-quality-gates
Python quality gates: zero tolerance for failing tests (no "pre-existing failure" excuse), and the pre-commit documentation-maintenance checklist. Use when finishing Python work, running a test suite, or preparing a Python commit.
prototype
Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.
plan-verification
Verifies an AA-MA plan from 6 adversarial angles (facts, assumptions, impact, acceptance criteria, implementation barriers, domain risk) and lists its defects. Use when asked to verify, check or review an AA-MA plan, and at aa-ma-plan Phase 4.5.
ops-mode
Activate full operational constraints mode for disciplined, efficient execution. Use when the user asks for ops mode.
operational-constraints
Activate comprehensive operational constraints for disciplined execution. Use at session start, before complex tasks, during planning phases, or when encountering friction. Enforces token efficiency, tool protocols, parallel execution, TDD, and system mapping.
logging-and-comments
Logging and code-comment standard for Python and Bash: library vs app logging, stderr vs stdout, no silent failures, run-level context for pipelines, why-comments, docstrings, constant rationale, TODO format, and the Ruff rules that enforce it. Use when writing or reviewing any script, CLI, hook, pipeline, or library code, or when adding try/except, || true, or 2>/dev/null.
llm-output-safety
Production safety requirements for pipelines that put LLM-generated text into client-facing outputs: non-Latin character sanitization, programmatic citation integrity, and treating recurring issues as architectural deficiencies. Use when generating reports, exports, or any client-facing document from LLM output.