Create comprehensive Architectural Decision Records (ADRs). Researches the destination directory to detect existing template conventions, gathers context, determines next ADR number, generates the ADR, validates completeness, and saves. Supports multiple ADR formats (MADR, Nygard, Alexandrian, project canonical). Use when documenting technical decisions or creating new ADR files.

Multi-agent debate orchestration for Architecture Decision Records. Automatically triggers on ADR create/edit/delete. Coordinates architect, critic, independent-thinker, security, analyst, and high-level-advisor agents in structured debate rounds until consensus.

Load-bearing design decisions for this repo as a contract you check before changing anything. Covers the asymmetric generation seam, source-of-truth per tree, hook runtime failure policy, memory tiers, plugin surfaces, invariants, and known-weak points. Use when you say `which tree is canonical`, `architecture contract`, `why is this designed this way`. Do NOT use for operating the build pipeline (use `ai-agents-generation-and-release`) or CI triage (use `ai-agents-debugging-playbook`).

Catalog of every configuration axis in this repo, env vars, commit markers, frontmatter keys, QA skip verdicts, and escape hatches, each with its enforcement point and abuse story, plus the checklist for adding a new flag safely. Use when you say `what does SKIP_LSP_GATE do`, `list escape hatches`, `can I skip this gate`, `add a config flag`. Do NOT use for hook runtime behavior (use `agent-harness-reference`) or change gating policy (use `ai-agents-change-control`).

Symptom-to-triage playbook for this repo's recurring failures. Blocked pushes, LSP warmup blocks, drift gate reds, plugin bump reds, coverage pin trips, hook exit 143, session NON_COMPLIANT. Maps each symptom to a first command, discriminating experiment, fix path, and trap. Use when you say `triage this failure`, `why is my push blocked`, `debug this CI red`. Do NOT use for incident history (use `ai-agents-failure-archaeology`) or measurement tools (use `ai-agents-diagnostics-toolkit`).

Prove-it methods for this repo. Six recipes for runtime-contract probes, guard and threshold calibration, eval A/B, docs-vs-reality audits, reproduce-on-main CI triage, and negative-control test design, each with a worked example from repo history. Use when you say `probe the runtime contract`, `calibrate this guard`, `prove it empirically`. Do NOT use for the portability battle plan (use `ai-agents-portability-campaign`) or evidence standards (use `ai-agents-validation-and-qa`).

Operate the ai-agents generation and release machinery, covering the seven build_all.py generators, generate_agents.py, sync_plugin_lib.py, the drift gates, three plugin.json semver bumps, and the npm publish path. Use when you say `regenerate the mirrors`, `run the drift checks`, `bump the plugin version`, `release the npm cli`. Do NOT use for environment setup (use `ai-agents-build-and-env`) or architecture rationale (use `ai-agents-architecture-contract`).

Executable decision-gated campaign for the cross-harness portability problem, keeping generated Copilot CLI plugin hooks honoring the empirically settled runtime contract (cwd, plugin-root anchor, payload casing, kill budget). Use when you say `run the portability campaign`, `port hooks to a new harness`, `copilot hook timeout regression`. Do NOT use for harness fact lookups (use `agent-harness-reference`) or generic probe recipes (use `ai-agents-empirical-probe-toolkit`).

What counts as evidence in ai-agents and how to produce it. Covers the TESTING-RIGOR pos+neg+edge bar, test layout and collection reality, coverage proof commands, runtime-contract tests with negative controls, and ADR-034 QA skip semantics at session end. Use when you say `what counts as evidence`, `how do I test this change`, `run skill tests`, `can I skip QA`. Do NOT use for CI failure triage (use `ai-agents-debugging-playbook`) or measurement tooling (use `ai-agents-diagnostics-toolkit`).

Identify code ownership before modifying validators or linters. Checks file headers for provenance indicators, reviews documentation, and determines provenance as UPSTREAM, LOCAL, VENDOR, or UNKNOWN. Prevents accidental modification of upstream tools.

Autonomous PR monitor and fixer per docs/autonomous-pr-monitor.md. Triages open PRs by tier, addresses thread feedback, fixes CI failures, and enables auto-merge when the 4-condition Ready-to-Merge gate passes.

Detect and stop manufactured work after a deliverable appears done. Use when a worker has produced a plan, issue, PR, backlog item, research artifact, or follow-up task and you need to verify it was demanded by a real user, acceptance criterion, or blocked decision instead of reward-seeking activity.

Input adapter that extracts a book's method into a structured payload and hands it off to SkillForge. Use when an operator wants to turn a methodology-bearing book (The Mom Test, Make It Stick, Influence, The Pragmatic Programmer, etc.) into one or more executable skills without hand-crafting the SkillForge prompt or bypassing SkillForge's triage and review gates.

**Created**: 2026-02-07 **Location**: `.claude/skills/buy-vs-build-framework/` **Status**: Production-ready **Tier**: 4 (Principal/VP level) **Timelessness**: 9/10

Strategic framework for evaluating build, buy, partner, or defer decisions with four-phase process, tiered TCO analysis, and integration with decision quality tools

Design and document chaos engineering experiments. Guide steady state baseline, hypothesis formation, failure injection plans, and results analysis. Use for resilience testing, game days, failure injection experiments, and building confidence in system stability.

Investigate historical context of existing code, patterns, or constraints before proposing changes. Automates git archaeology, PR/ADR search, and dependency analysis to prevent removing structures without understanding their purpose.

Assess code maintainability through 5 foundational qualities (cohesion, coupling, encapsulation, testability, non-redundancy) with quantifiable scoring rubrics. Works at method/class/module levels across multiple languages. Produces markdown reports with remediation guidance.

Execute CodeQL security scans with language detection, database caching, and SARIF output. Use when performing static security analysis on Python or GitHub Actions code.

Gather comprehensive context from Forgetful Memory, Context7 docs, and web sources before planning or implementation. Use when starting complex tasks requiring multi-source context.