40a82ccdb4
Stop hook fallback antok 200K-vindu. På Opus 4.7 (faktisk 1M) kunne auto-handoff fyre 5–7x for tidlig — estimert 70% når reell bruk var ~14%. Erstatter enkel fallback med 4-stegs resolution-kjede: 1. payload.context_window.used_percentage (autoritativ) 2. payload.context_window.context_window_size + transcript-estimat 3. MODEL_WINDOWS[payload.model.id] + estimat 4. FALLBACK_WINDOW=1_000_000 + estimat (2026-default) additionalContext-meldinger inkluderer nå [kilde: <source>] for innsyn. Brief som kilde-artefakt i docs/brief-context-window-detection.md. 6 nye tester (57 totalt). Ingen regresjoner.
235 lines
21 KiB
Markdown
235 lines
21 KiB
Markdown
# ktg-plugin-marketplace
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Open-source Claude Code plugins for AI-assisted development, security, and planning.
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Built for my own Claude Code workflow and shared openly for anyone who finds them useful. Solo project — bug reports and feature requests are welcome, pull requests are not accepted.
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## AI-generated code disclosure
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All code in this marketplace is generated by Claude Code through a dialog-based process. I direct, review, test, and validate; Claude writes. Every commit reflects this — treat the plugins as AI-authored, human-curated.
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## Installation
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```bash
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claude plugin marketplace add https://git.fromaitochitta.com/open/ktg-plugin-marketplace.git
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```
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Then open Claude Code and type `/plugin` to browse and install plugins from the marketplace.
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## Compatibility
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- Claude Code CLI, desktop app, and IDE extensions
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- macOS, Linux, Windows
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- No external dependencies (all scanners and hooks are self-contained)
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---
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## Plugins
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### [LLM Security](plugins/llm-security/) `v7.3.1`
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Security scanning, auditing, and threat modeling for agentic AI projects.
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Built on OWASP LLM Top 10 (2025), OWASP Agentic AI Top 10, and the AI Agent Traps taxonomy (Google DeepMind, 2025). Three layers of protection:
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- **Automated enforcement** — 9 hooks that block dangerous operations in real time (prompt injection, secrets in code, destructive commands, supply chain guardrails, transcript scanning before context compaction)
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- **Deterministic scanning** — 23 Node.js scanners (10 orchestrated + 13 standalone) for byte-level analysis: Shannon entropy, Unicode codepoints, typosquatting detection, taint flow, DNS resolution, git forensics, AI-BOM, attack simulation, IDE extension prescan (VS Code + JetBrains — URL fetch from Marketplace / OpenVSX / direct VSIX / JetBrains Marketplace, hardened ZIP extractor for zip-slip / symlinks / bombs, plus OS sandbox via `sandbox-exec` / `bwrap` so the kernel enforces FS confinement), MCP cumulative-drift baseline reset (E14 — sticky baseline catches slow-burn rug-pulls). Bash-normalize T1-T6 for obfuscation-resistant denylists
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- **Advisory analysis** — 20 commands that scan, audit, and model threats with structured reports, letter grades, and actionable remediation
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- **Enterprise governance** — Compliance mapping (EU AI Act, NIST AI RMF, ISO 42001), SARIF 2.1.0 output, structured audit trail, policy-as-code, standalone CLI
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- **v8.0.0 env-var deprecation runway (D3, v7.3.0)** — Hook configuration has historically been split between process env-vars and the team-distributable `.llm-security/policy.json` file. Until v7.3.0 the two surfaces could disagree silently. The new `getPolicyValueWithEnvWarn()` helper in `scanners/lib/policy-loader.mjs` now emits a one-time-per-process stderr line whenever both surfaces are explicitly set:
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- Affected pairs: `LLM_SECURITY_INJECTION_MODE`↔`injection.mode`, `LLM_SECURITY_TRIFECTA_MODE`↔`trifecta.mode`, `LLM_SECURITY_ESCALATION_WINDOW`↔`trifecta.escalation_window` (new key in `DEFAULT_POLICY`), `LLM_SECURITY_AUDIT_LOG`↔`audit.log_path`
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- Env still wins through the v7.x window — no behaviour change today, only a runway signal
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- Suppress headless-log noise with `LLM_SECURITY_DEPRECATION_QUIET=1`
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- Teams should converge on `policy.json` for distributable configuration before v8.0.0 removes the env-var path
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- **Opus 4.7 aligned** — Agent instructions rewritten for literal instruction-following (system card §6.3.1.1), defense-in-depth posture per §5.2.1, production hardening guide
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Key commands: `/security posture`, `/security audit`, `/security scan`, `/security ide-scan`, `/security threat-model`, `/security plugin-audit`
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6 specialized agents · 23 scanners · 9 hooks · 20 knowledge docs · 1768 tests
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→ [Full documentation](plugins/llm-security/README.md)
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---
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### [Config-Audit](plugins/config-audit/) `v4.0.0`
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Configuration intelligence for Claude Code — health checks, feature discovery, auto-fix, active-config inventory, and Opus-4.7-aware token-cost analysis.
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Claude Code reads instructions from 7+ file types across multiple scopes. This plugin tells you what's wrong, what's missing, what's silently conflicting, what's actually loaded, and where you're burning tokens unnecessarily:
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- **Health** — 8 deterministic scanners verify correctness across every configuration file (broken imports, deprecated settings, conflicting rules, permission contradictions, and Opus-4.7-era token waste)
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- **Opportunities** — context-aware recommendations for Claude Code features you're not using
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- **Action** — auto-fix with mandatory backups, syntax validation, rollback support, and human-in-the-loop workflow
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- **What's active** — read-only inventory of plugins, skills, MCP servers, hooks, and CLAUDE.md cascade for a repo, with token estimates
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- **Token hotspots** — `/config-audit tokens` ranks files by estimated waste against 4 Opus-4.7 patterns (cache-breaking volatile content, redundant tool permissions, deep import chains, sonnet-era setups)
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Key commands: `/config-audit posture`, `/config-audit feature-gap`, `/config-audit fix`, `/config-audit whats-active`, `/config-audit tokens`
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6 agents · 9 scanners · 17 commands · 543+ tests
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→ [Full documentation](plugins/config-audit/README.md)
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---
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### [Ultra {brief | research | plan | execute} - local](plugins/ultraplan-local/) `v3.1.0`
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Deep requirements gathering, research, implementation planning, and self-verifying execution with specialized agent swarms, adversarial review, and failure recovery.
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Four commands, one pipeline with clear division of labor:
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- **`/ultrabrief-local`** — Capture intent. Dynamic, quality-gated interview: a section-driven completeness loop (Phase 3) followed by a `brief-reviewer` stop-gate (Phase 4, max 3 review iterations). Required sections must reach an initial-signal gate AND pass review across completeness, consistency, testability, scope clarity, and research-plan validity before `brief.md` is written. Identifies research topics with copy-paste-ready `/ultraresearch-local` commands. Optional auto-orchestration runs research + planning in foreground. Always interactive.
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- **`/ultraresearch-local`** — Gather context. Deep multi-source research with triangulation: 5 local agents + 4 external agents + Gemini bridge, producing structured briefs with confidence ratings. Makes no build decisions.
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- **`/ultraplan-local`** — Transform intent into an executable contract. Per-step YAML manifests (`expected_paths`, `commit_message_pattern`, `bash_syntax_check`). Plan-critic is a hard gate on manifest quality. Requires a task brief as input (`--brief` or `--project`). Auto-discovers `architecture/overview.md` when the optional `ultra-cc-architect` plugin is installed and cross-references its `cc_features_proposed` against exploration findings.
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- **`/ultraexecute-local`** — Execute the contract disciplined. Manifest-based verification, independent Phase 7.5 audit from git log + filesystem (ignores agent bookkeeping), Phase 7.6 bounded recovery dispatch for missing steps. Step 0 pre-flight catches sandbox push-denial before any work. `--validate` mode offers a fast schema-only sanity-check between planning and execution.
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All artifacts land in one project directory: `.claude/projects/{YYYY-MM-DD}-{slug}/` contains `brief.md`, `research/NN-*.md`, `plan.md`, `sessions/`, and `progress.json`. `--project <dir>` works across `/ultraresearch-local`, `/ultraplan-local`, and `/ultraexecute-local`.
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v3.0.0 extracts the Claude-Code-specific architecture phase to a separate plugin (`ultra-cc-architect`, see below). The planning pipeline now stays technology-agnostic; CC-feature matching becomes opt-in. The plan command still auto-discovers `architecture/overview.md` if the new plugin is installed — the contract is filesystem-level, not code-level. Non-breaking for users of brief/research/plan/execute. See `plugins/ultraplan-local/CHANGELOG.md` for migration steps.
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v2.4.0 (breaking, default behavior) removes background mode. The commands now run foreground in the main context because the harness does not expose the Agent tool to sub-agents — background orchestrators silently degraded the swarm to inline reasoning without external research tools. The `--fg` flag is preserved as a no-op alias for backward compatibility. Source: github.com/anthropics/claude-code/issues/19077.
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v2.1 (non-breaking) replaced the hardcoded Q1–Q8 interview with a dynamic, quality-gated loop; `brief-reviewer` emits machine-readable per-dimension JSON scores so `/ultrabrief-local` can use it as an internal stop-gate. v2.0 (breaking) extracted the interview from planning: briefs are reviewable artifacts that downstream agents (`brief-reviewer`, `plan-critic`, `scope-guardian`) validate independently. `/ultraplan-local` requires `--brief` or `--project`. See `plugins/ultraplan-local/MIGRATION.md`.
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v1.7 self-verifying chain (preserved): a step may not be marked `completed` unless its manifest verifies. v1.8 Opus 4.7 literalism fixes (preserved): literal Step+Manifest template, forbidden narrative headers, schema self-check.
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v3.1.0 (in progress) adds a `lib/`-tree of zero-dep validators (`brief-validator`, `research-validator`, `plan-validator`, `progress-validator`, `architecture-discovery`) wired into the four commands as CLI shims, plus 109 `node:test` cases and a doc-consistency invariant test. The Phase 5.5 schema self-check now runs as `node lib/validators/plan-validator.mjs --strict` instead of three `grep -cE` calls — same checks, single source of truth, machine-readable error codes. Architecture discovery treats the `ultra-cc-architect` contract as drift-WARN, never drift-FAIL. Forking the plugin? `npm test` is the readiness gate.
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v3.1.0 also adds: `docs/HANDOVER-CONTRACTS.md` as the single source of truth for the 5 pipeline handovers; PreCompact-hook (`pre-compact-flush.mjs`, CC v2.1.105+) that fixes the documented progress.json drift bug — `--resume` now works after long conversations; UserPromptSubmit-hook that sets session titles `ultra:<command>:<slug>` for headless multiplexing (CC v2.1.94+); PostToolUse-hook that captures Bash `duration_ms` per call (CC v2.1.97+); semantic plan-critic rubric that catches paraphrased deferred decisions ("implement as needed", "wire it up") instead of just exact-string blacklist; `examples/01-add-verbose-flag/` showing a calibrated end-to-end pipeline run; `SECURITY.md` boilerplate; `docs/architect-bridge-test.md` smoke checklist.
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Defense-in-depth security: plugin hooks block destructive commands and sensitive path writes, prompt-level denylist works in headless sessions, pre-execution plan scan catches dangerous commands before they run, scoped `--allowedTools` replaces `--dangerously-skip-permissions` in parallel sessions. Recommended hardening: `disableSkillShellExecution: true` for fork-ers handling untrusted plans (CC v2.1.91+).
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Modes: default, brief-driven, project-scoped, research-enriched, foreground, quick, decompose, export
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19 specialized agents · 4 commands · 4 plugin hooks · No cloud dependency
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→ [Full documentation](plugins/ultraplan-local/README.md) · [Migration guide](plugins/ultraplan-local/MIGRATION.md)
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---
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### [Ultra CC Architect](plugins/ultra-cc-architect/) `v0.1.0` `🚧 pre-release`
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Match a task brief and research against available Claude Code features, with brief-anchored rationale and explicit coverage gaps. Extracted from `ultraplan-local` v2.4.0 in 2026-04-30.
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Two commands, both Claude-Code-specific:
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- **`/ultra-cc-architect-local`** — Reads `brief.md` + `research/*.md` (typically produced by `ultraplan-local`), consults the seeded `cc-architect-catalog` skill (hooks, subagents, skills, output styles, MCP, plan mode, worktrees, background agents), and produces `architecture/overview.md` with brief-anchored rationale plus `architecture/gaps.md` with issue-ready drafts for missing catalog entries. Hallucination gate (enforced by `architecture-critic`) blocks proposals for features not covered by the catalog.
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- **`/ultra-skill-author-local`** *(skill-factory Fase 1)* — Generates one `cc-architect-catalog` draft skill from a curated local source file with IP-hygiene enforcement. Sequential pipeline: `concept-extractor` → `skill-drafter` → `ip-hygiene-checker`. Drafts land in `skills/cc-architect-catalog/.drafts/` for manual review and `mv` promotion. Pure-Node n-gram containment scorer (`scripts/ngram-overlap.mjs`) enforces verdict bands; rejected drafts are deleted.
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The plugin sits between `/ultraresearch-local` and `/ultraplan-local` in the typical workflow. `ultraplan-local` v3.0.0+ auto-discovers `architecture/overview.md` when present — install both plugins to keep the full pipeline (brief → research → architect → plan → execute) working.
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**Pre-release because:** catalog is thin (11 seed skills across 8 features), decision-layer is intentionally empty, skill-factory has only Fase 1 (Fase 2/3 unbuilt), and `feature-matcher` falls back to a hardcoded list when the catalog is sparse. v1.0 ships when the catalog is dense enough that the fallback list can be removed.
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Slug convention: `<cc_feature>[-<qualifier>]-<layer>.md`. Unqualified slugs are the canonical baseline per `(feature, layer)` pair; qualified slugs cover specific sub-patterns. `feature-matcher` prefers the unqualified baseline unless the brief justifies a variant. Slug collisions with approved skills are a hard error. `skill-drafter` warns before overwrite.
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8 specialized agents · 2 commands · 1 skill (CC-feature catalog, 11 seeds) · 1 IP-hygiene script
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→ [Full documentation](plugins/ultra-cc-architect/README.md)
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---
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### [AI Psychosis](plugins/ai-psychosis/) `v1.0.0`
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Meta-awareness tools that counteract sycophancy, reinforcement loops, and compulsive AI interaction patterns.
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AI assistants are structurally optimized to be agreeable. This creates reinforcement loops where productive collaboration is often a mirror showing you what you want to see. Research documents psychotic episodes triggered by sustained AI interaction in individuals with no prior psychiatric history.
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- **Layer 1 — Behavioral instructions** — SKILL.md rules that modify Claude's behavior: no unearned affirmations, mandatory risk identification, pattern naming
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- **Layer 2 — Programmatic detection** — 4 hooks that measure session duration, dependency language, rapid-fire bursts, edit ratios, and late-night usage with progressive alerts
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- **Layer 3 — Interaction reports** — `/interaction-report` slash command for aggregated session statistics across configurable timeframes (weekly, monthly, all-time). Opt-in
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- **Layer 4 — Contemplative references** — optional references to contemplative approaches when interaction flags are elevated. Opt-in
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Research-informed thresholds. Alerts are progressive and never blocking. Privacy-first: prompt text is never logged. Layers 3 and 4 are off by default.
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1 skill · 1 command · 4 hooks
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→ [Full documentation](plugins/ai-psychosis/README.md)
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---
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### [Graceful Handoff](plugins/graceful-handoff/) `v2.1.0`
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Auto-trigger session handoff at context threshold. Manual `/graceful-handoff` always works as backup. Built for Opus 4.7.
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When you hit 60-70% context and have to start a new session, three things usually get rushed or forgotten: summarizing state, committing finished work, and writing a continuation prompt. v2.0 removes all three from the user's hands.
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- **Auto-trigger via Stop hook** — at estimated ≥70% context, writes artifact + commits (push remains user-triggered: irreversible operations stay manual)
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- **statusLine hint** — display-only warning at 60% and urgent reminder at 70% (never runs git, safe per research)
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- **SessionStart auto-load** — on `--resume` / `compact`, handoff content is injected into the new session via `additionalContext`; no manual `cat` needed
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- **Skill-architecture** — `disable-model-invocation: true` so Claude can't autonomously invoke the side-effect-bearing flow; user triggers manually or hooks call the pipeline directly
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- **Deterministic JSON pipeline** — `scripts/handoff-pipeline.mjs` returns structured JSON; tests run without LLM involvement
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- **Explicit staging** — pipeline stages ONLY the artifact (never `git add -A`, regression-tested)
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- **No subagents, no web** — under 60s budget; pinned to Sonnet 4.6 to free Opus for the next session
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Key command: `/graceful-handoff [topic-slug] [--no-commit] [--no-push] [--dry-run]`
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3 hooks · 1 skill · 1 pipeline · 36 tests · BREAKING from v1.0
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→ [Full documentation](plugins/graceful-handoff/README.md)
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---
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### [MS AI Architect — Azure AI and Microsoft Foundry](plugins/ms-ai-architect/) `v1.8.0` `🇳🇴 Norwegian`
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Microsoft AI solution architecture guidance for Norwegian public sector and enterprise.
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Meet Cosmo Skyberg — a structured architect persona who understands the problem before recommending technology. Every recommendation is grounded in 387 reference documents and verified against live Microsoft Learn documentation via MCP:
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- **Structured advisory** — 7-phase methodology from business need to architecture recommendation and optional diagram
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- **Regulatory assessments** — ROS analysis (NS 5814), DPIA/PVK, security scoring (6×5), EU AI Act classification, cost estimation in NOK (P10/P50/P90)
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- **Norwegian public sector** — Digdir architecture principles, Utredningsinstruksen, NSM, Schrems II data residency, EU AI Act compliance workflow
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- **Automated freshness** — sitemap-based change detection polls Microsoft Learn weekly, flags which reference files need updating based on source page changes, and discovers new relevant pages
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Key commands: `/architect`, `/architect:ros`, `/architect:security`, `/architect:dpia`, `/architect:utredning`, `/architect:cost`
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12 specialized agents · 24 commands · 5 skills (387 reference docs) · 2 hooks · sitemap-based KB monitoring
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→ [Full documentation](plugins/ms-ai-architect/README.md)
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---
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### [LinkedIn Thought Leadership](plugins/linkedin-thought-leadership/) `v1.2.0`
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Build authentic LinkedIn authority through algorithmic understanding, strategic consistency, and AI-assisted content creation.
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Updated for the January 2026 360Brew algorithm change, which validates your creator profile before distributing content. v1.2.0 reduces friction: auto-clipboard on all content commands, max 2 interactive steps per post, deterministic state management, MCP image carousel pipeline, progressive onboarding, and iCal calendar integration for batch scheduling.
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- **Guided onboarding** — `/linkedin:onboarding` walks new users through profile → setup → first post in one flow
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- **360Brew profile optimization** — audit your profile against LinkedIn's creator validation criteria
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- **Full content pipeline** — ideation, drafting, publishing, 48-hour monitoring, and analytics
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- **Content Matrix System** — 40+ post ideas from a single topic using 8 universal angles and 48 industry-specific variants
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- **Voice training** — learns your authentic writing style and detects drift with 6-dimension scoring
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- **Analytics pipeline** — import LinkedIn CSV exports, weekly/monthly reports, day-of-week heatmap
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- **Growth strategy** — phase-specific guidance from foundation (0-1K followers) through authority (10K+)
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Key commands: `/linkedin:onboarding`, `/linkedin:post`, `/linkedin:quick`, `/linkedin:carousel`, `/linkedin:react`, `/linkedin:report`
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16 specialized agents · 27 commands · 6 skills · 9 hooks · 24 reference docs
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→ [Full documentation](plugins/linkedin-thought-leadership/README.md)
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---
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### [OKR for Public Sector](plugins/okr/) `v1.3.0` `🇳🇴 Norwegian`
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Turn strategy into measurable goals. An AI coach that learns your organization, tracks progress across cycles, and guides you from first OKR to organizational mastery.
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Most OKR tools explain methodology. This plugin *knows your organization*. After a one-time onboarding conversation, it remembers your maturity level, strategic goals, current OKR, and cultural challenges. Every interaction builds on that knowledge — so you spend time on strategy, not re-explaining context.
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- **Strategy to OKR** — transform goals from virksomhetsplan, tildelingsbrev, or any strategic document into well-structured OKR with guided writing, quality checks, and alignment scoring
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- **Gap analysis** — `/okr:gap` compares your strategic documents against current OKR and shows what's covered, what's missing, and what to do about it
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- **Cross-cycle learning** — `/okr:analyse` tracks score trends, recurring antipatterns, and alignment progress across cycles with visual charts
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- **Proactive coaching** — automatically tells you where you are in the cycle and what to focus on — progress checks mid-cycle, retrospective prep near the end
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- **19 antipattern detection** — catches sandbagging, activity-disguised-as-KR, set-and-forget, and 16 more named failure modes before they take root
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- **Built for norsk offentlig sektor** — 4-month tertials, DFO terminology, tillitsvalgt involvement, Riksrevisjon-ready documentation, governance chain from Stortingsmelding to team OKR
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Key commands: `/okr:skriv`, `/okr:kvalitet`, `/okr:gap`, `/okr:analyse`, `/okr:kaskade`, `/okr:sporing`, `/okr:governance`, `/okr:oppsett`
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7 agents · 10 commands · 4 hooks · 16 reference docs
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→ [Full documentation](plugins/okr/README.md)
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---
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## License
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MIT
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