By mtrense
Bootstraps and maintains an AI-consumable map of an existing codebase: top-level + per-module CODEBASE.md, architecture assessment, and derived CLAUDE.md/AGENTS.md rules.
Extracts the language-level public API surface of a module — exported symbols, types, functions, classes, traits — using language-aware tooling first (cargo public-api, tsc --emitDeclarationOnly, go doc, pdoc) and import-grep as fallback. Returns a structured listing. Used during a per-module survey.
Computes inbound and outbound dependencies for a module by running the project's native dependency tooling (cargo tree, npm ls, pip-deptree, go mod graph, mvn dependency:tree, etc.). Returns a structured report. Skips cleanly if no native tool is available. Use during a per-module survey to populate the Dependencies section of CODEBASE.md.
Surveys CI/CD pipelines, container builds, deploy manifests, secrets handling, observability hooks, and logging libraries — without executing anything. Returns a structured inventory of what runs where and what watches it. Used during the per-module survey and the repo-level CODEBASE.md.
Discovers raw structural signals about an unknown codebase: build manifests, workspace declarations, top-level layout, and language mix. Returns a structured report. Does NOT infer module boundaries — that synthesis is left to the caller. Use for the first pass of a codebase survey.
Audits a module's test situation: discovers test files, runs the project's test runner in collect-only / list mode to count tests by layer (unit / integration / e2e), and surfaces coverage when readily available. Returns pyramid-shape numbers, not opinions about adequacy. Used during a per-module survey.
Cross-cutting architecture pass after per-module surveys are complete. Reads every <module>/CODEBASE.md and the top-level CODEBASE.md, looks for domain- boundary leaks, coupling hotspots, deviations between stated and actual architecture, and stack inconsistencies. Writes findings to docs/codebase/assessment.md with each finding tagged kind:rule or kind:observation, and synthesises docs/codebase/architecture.md, tech-stack.md, and operations.md from the same inputs. Run after the module burndown, before /codebase-derive-instructions.
Read the assembled codebase survey (CODEBASE.md files, docs/codebase/*.md, assessment findings) and produce a lean, source-anchored CLAUDE.md at the repo root plus one per module that has rules. Lifts kind:rule findings only; observations stay in assessment.md. Verifies length budgets, rule duplication, and code-style leaks before writing. If AGENTS.md exists at the repo root, derive into AGENTS.md instead and write a thin CLAUDE.md that imports it.
Bootstrap a codebase survey: delegate raw structural discovery to the structural-discovery subagent, synthesize the module map (judgment call — stays in the main session), then write the top-level CODEBASE.md plus per-module stub files. Run once per repository, before per-module deep-dives.
Deep-dive survey of one module. Spawns the dep-grapher, api-surface-extractor, wire-api-extractor, test-auditor, and ops-detective subagents in parallel, then assembles the module's CODEBASE.md from their reports. Idempotent — re-running rewrites the file. Trigger after /codebase-survey-init has produced module stubs, or whenever a single module needs a fresh detailed survey. Argument: the module path (relative to repo root).
Incremental refresh of an existing codebase survey. With no argument, each module is diffed from its own recorded surveyed_sha to HEAD. With a commit range or PR# argument, that range is used uniformly. Maps changed paths to affected module docs, dispatches narrowly-scoped subagents for only those modules, then bumps each touched module's surveyed_sha. Model-invocable so it can be wired to a post-merge hook later.
Uses power tools
Uses Bash, Write, or Edit tools
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A collection of prompt-based skills for Claude Code that add structured workflows for software engineering and research.
Skills are markdown files with YAML frontmatter that Claude loads as playbooks. Each skill provides a /slash-command — you invoke it, and Claude follows the skill's instructions to guide you through a specific workflow phase.
This repo can be installed two ways: as a Claude Code plugin marketplace (recommended for end users) or via the legacy symlink installer (recommended for developing/iterating on the skills themselves).
The repo root carries a .claude-plugin/marketplace.json catalog (mtrense-skills). Each workflow family is exposed as a separately-installable plugin with its own <workflow>/.claude-plugin/plugin.json manifest.
/plugin marketplace add mtrense/skills
/plugin install milestone-driven@mtrense-skills
/plugin install research@mtrense-skills
/plugin install codebase-survey@mtrense-skills
/plugin install common@mtrense-skills
Updates: /plugin marketplace update. No version field is pinned, so each commit on main is treated as a new version.
# Install every workflow globally (~/.claude/skills/ + ~/.claude/agents/)
./install.sh all
# Install just one workflow globally
./install.sh milestone-driven
# Install one workflow into a specific project
./install.sh research /path/to/project
The first argument is the workflow name (codebase-survey, common, milestone-driven, research) or all. The optional second argument is the install target (defaults to $HOME). The installer creates symlinks, so skills stay up to date as you pull changes.
A phased cycle for building software, from idea through implementation to closeout. Each phase produces a specific artifact that feeds into the next.
| Phase | Command | What it does | Produces |
|---|---|---|---|
| 0 | /project-inception | Socratic dialogue to discover project vision and goals | README.md |
| 1 | /strategic-planning | Sharpen ideas into well-defined, testable milestones | ROADMAP.md entries |
| 2 | /milestone-breakdown | Decompose a milestone into ordered, independently testable tasks | PLAN.md |
| 3 | /task-implementation | Implement one task using strict TDD (tests first, then code) | Passing code + tests |
| 3 | /implementation-cycle | Run task-implementation + commit in fresh subagents per task to keep the main session clean | Passing code + commits |
| 4 | /milestone-closing | Verify success criteria, document results, reset for next cycle | Updated ROADMAP.md |
| - | /commit | Craft a conventional commit from staged/unstaged changes | Git commit |
Typical flow: inception (once) -> planning -> breakdown -> implementation (repeat per task) -> closing -> back to planning.
The milestone-driven workflow uses two bundled subagents: milestone-scout (delegated codebase reconnaissance for milestone-breakdown) and task-worker (per-task task-implementation + commit worker for implementation-cycle). Both live in milestone-driven/agents/ and are installed alongside the workflow's skills.
A multi-phase system for building structured knowledge bases with source verification and quality auditing.
| Phase | Command | What it does |
|---|---|---|
| 1 | /research-inception | Create project structure: INDEX.md, DECISIONS.md, glossary, topic stubs |
| - | /research-add-topic | Add a new topic (directory + chapter stubs) to an existing project |
| - | /research-add-chapter | Add new chapter stubs to an existing topic directory |
| 2 | /research-inquiry | Add section outlines with RESEARCH directives to a chapter |
| 3 | /research-investigation | Write content for one section; delegates the search-fetch-verify loop to the source-investigator subagent |
| 4 | /research-audit-consistency | Check cross-topic contradictions; insert AUDIT directives |
| 4 | /research-audit-coverage | Check gaps relative to the research plan; insert AUDIT directives |
| 4 | /research-audit-quality | Check depth and sourcing adequacy; insert AUDIT directives. Fans out per-topic analysis to quality-auditor in parallel |
| 4 | /research-audit-coherence | Check narrative flow; insert AUDIT directives. Fans out per-topic analysis to coherence-auditor in parallel |
| 5 | /research-refine | Resolve audit findings (correct, expand, condense, restructure) |
| 6 | /research-restructure | Structural changes: split, merge, promote, or demote topics |
| 7 | /research-glossary-sync | Reconcile glossary against current topic content. Fans out per-topic candidate extraction to term-extractor in parallel |
npx claudepluginhub mtrense/skills --plugin codebase-surveyFour-phase milestone-driven build cycle: strategic planning, milestone breakdown, TDD task implementation, and milestone closing.
Multi-phase research workflow for building cited, audited knowledge bases — inquiry, investigation, consistency/coverage/quality/coherence audits, refinement, and glossary sync.
Cross-workflow utilities: /commit (the single commit point for all workflows), /pr, /audit-context, and /deckset.
Make your AI agent code with your project's architecture, rules, and decisions.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
AI-powered wiki generator for code repositories. Generates comprehensive, Mermaid-rich documentation with dark-mode VitePress sites, onboarding guides, deep research, and source citations. Inspired by OpenDeepWiki and deepwiki-open.
Claude + Obsidian knowledge companion. Sets up a persistent, compounding wiki vault (Karpathy's LLM Wiki pattern). v1.7 "Compound Vault" + v1.8 methodology modes close 5 of 5 priority gaps from the May 2026 compass artifact. Ships: substrate alignment with kepano/obsidian-skills, default Obsidian CLI transport, hybrid retrieval (contextual prefix + BM25 + cosine rerank per Anthropic's Sept 2024 research), per-file advisory locking for multi-writer safety, pre-commit verifier agent, AND methodology modes (LYT / PARA / Zettelkasten / Generic) for first-class organizational support no other Claude+Obsidian competitor offers. v1.7.x audit closure: every BLOCKER + HIGH + MEDIUM + LOW finding from the v1.7.0 audit is CLOSED or DEFERRED-with-rationale. Optional DragonScale Memory extension (log folds, deterministic addresses, semantic tiling lint, boundary-first autoresearch).
Complete AI coding workflow system. Self-correcting memory + persistent FTS5-indexed research wikis + auto-research loop + multi-LLM council on a single SQLite store. 33 skills, 8 agents, 22 commands, 37 hook scripts across 24 events. Cross-agent via SkillKit.
Comprehensive C4 architecture documentation workflow with bottom-up code analysis, component synthesis, container mapping, and context diagram generation