accounts
無料Manage multiple Claude Code accounts: add, list, check, launch, and install shell aliases for 10+ isolated CLAUDE_CONFIG_DIR profiles.
日本語の概要は準備中です。原文の説明を表示しています。
Assessment: read-only inspection, codebase overview, value analysis, health checks, ADR consultation, decision analysis, multi-perspective critique.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Seven modes for read-only analysis and decision support. Match the request to a mode, then follow that mode's phases.
| Request pattern | Mode |
|---|---|
| Inspect, browse, explore without changing | Read-Only Inspection |
| Onboard, overview, summarize repo, codebase structure | Codebase Overview |
| Repo value analysis, compare repos, what can we learn | Repo Value Analysis |
| Service status, health check, uptime, validate endpoints | Service Health Check |
| Consult on ADR, challenge design, architecture consultation | ADR Consultation |
| Help me decide, decision matrix, pros/cons, trade-offs | Decision Scoring |
| Critique ideas, devil's advocate, stress test, roast | Multi-Persona Critique |
Safe exploration without modifying files or system state.
Parse the request. Determine target scope (file, directory, service, system-wide). Clarify before proceeding if scope could match dozens of results.
Use read-only tools only.
Allowed: ls, find, wc, du, df, file, stat, ps, top -bn1,
uptime, free, pgrep, git status/log/diff/show/branch,
sqlite3 "SELECT ...", curl -s (GET only), date, env.
Forbidden: mkdir, rm, mv, cp, touch, chmod, chown,
git add/commit/push, file writes, INSERT/UPDATE/DELETE/DROP,
npm/pip/apt install, kill, systemctl restart.
Lead with the answer. Show supporting evidence. List files examined. All claims must cite evidence.
4-phase exploration producing an evidence-backed onboarding report. Read-only.
Read any .claude/CLAUDE.md or CLAUDE.md in the repo root first. Skip
sensitive files (.env, *.pem, *.key, credentials) silently.
Examine root directory. Identify project type from config files (package.json,
go.mod, pyproject.toml, pom.xml, Cargo.toml). Document: language,
framework, build system, dependencies. Load references/codebase-overview/exploration-strategies.md
for language-specific discovery commands.
Gate: Project type identified. Tech stack documented.
Discover entry points, core modules, data models, API surfaces, configuration,
tests. Limit 20 files per category. Map directory structure (exclude
node_modules/, venv/, vendor/, dist/, build/, __pycache__/).
Gate: Entry points, core modules, data layer, API surface, config, tests documented.
Identify design patterns with file evidence. Map 5-10 key abstractions. Trace a typical request through the full stack. Analyze last 10 commits. All paths absolute. All claims cite source files.
Gate: Patterns identified, abstractions mapped, data flow documented.
Generate report using references/codebase-overview/report-template.md.
Include "Where to Add New Code" section. Run post-exploration secret scan.
For deep-dive mode ("full picture"), launch 4 parallel domain agents via Task.
See references/codebase-overview/examples-and-errors.md for dispatch template.
Scripts: scripts/cartographer.py (quick), scripts/cartographer_omni.py
(100-metric), scripts/cartographer_ultimate.py (focused performance).
6-phase pipeline analyzing external repositories for adoptable ideas.
Parse input (GitHub URL, local path, org/repo). git clone --depth 1.
Categorize files into zones (skills, agents, hooks, docs, tests, config, code,
other). Cap zones at ~100 files.
Dispatch 1 Agent per zone (up to 8). Each reads EVERY file and produces:
component inventory, key techniques, notable patterns, gaps. Output to
/tmp/[REPO]-zone-[zone].md.
Gate: 75%+ agents returned.
Dispatch 1 Agent to catalog vexjoy-agent repo: agents, skills, hooks, scripts
with counts. Output to /tmp/self-inventory.md.
Read all zone findings and inventory. Build comparison table. Rate gaps:
HIGH/MEDIUM/LOW. Save draft to research-[REPO]-comparison.md.
For each HIGH/MEDIUM recommendation, dispatch 1 audit Agent to verify: ALREADY
EXISTS, PARTIAL, or MISSING. Skip with --quick.
Adjust recommendations from audit. Write final report: executive summary,
comparison table, already-covered, recommendations, verdict, next steps. Clean
/tmp/ files. Load references/repo-value-analysis/phase7-implement-template.md
for implementation dispatch.
Deterministic service monitoring: Discover-Check-Report. Never report healthy without verifying process status independently.
Locate service definitions: services.json, docker-compose, systemd units, or
user input. Build manifest: process pattern, health file, port, stale threshold
per service.
Per service: (1) pgrep -f "<pattern>" for process status, (2) parse health
file JSON for staleness/status/connections, (3) ss -tlnp "sport = :<port>"
for port.
| Condition | Status |
|---|---|
| Process not running | DOWN |
| Running + health file missing/stale | WARNING |
| Running + status=error | ERROR |
| Running + disconnected >30min | WARNING |
| Running + port not listening | ERROR |
| Running + healthy | HEALTHY |
Gate: All services evaluated with evidence.
Output summary (X/N healthy), highlight services needing action, provide copy-pasteable remediation. Never auto-restart without explicit flag.
For endpoint validation, load references/service-health-check/endpoint-validator.md.
For CVE source auditing, load references/service-health-check/cve-source-check.md.
3-agent parallel architecture consultation producing PROCEED or BLOCKED.
Locate ADR (user path, .adr-session.json, or ask). Validate via
adr-query.py. Read full ADR. Create adr/{adr-name}/ directory.
Gate: ADR read, path validated, consultation directory created.
Launch all 3 agents in ONE message. Load references/adr-consultation/agent-prompts.md
for prompt templates:
For complex decisions, add 2 more agents (see agent-prompts.md).
Gate: All agents returned and wrote to adr/{adr-name}/.
Read agent files from disk. Extract concerns to adr/{adr-name}/concerns.md.
Determine verdict: all PROCEED = strong consensus, any BLOCK = hard block,
mixed = significant concerns. Write adr/{adr-name}/synthesis.md. Issue
verdict per references/adr-consultation/consultation-patterns.md.
Weighted scoring for 2-4 options. Runs inline (no fork).
State decision in one sentence. List 2-4 options. Eliminate non-starters first.
Default weights (adjust per domain -- load references/decision-helper/decision-archetypes.md
for build-vs-buy, database, cloud, framework, API, or operational tooling):
| Criterion | Weight | Measures |
|---|---|---|
| Correctness | 5 | Solves the actual problem |
| Complexity | 3 | Added complexity (lower = better) |
| Maintainability | 3 | Ease of change/debug |
| Risk | 3 | Failure mode severity |
| Effort | 2 | Implementation time |
| Familiarity | 2 | Team comfort |
| Ecosystem | 1 | Library/community support |
Lock weights before scoring. Do not adjust after seeing results.
Rate each option 1-10 per criterion with one-sentence justification. Calculate
sum(score * weight) / sum(weights).
All scores <6.0: no good option -- explore alternatives. Top two within 0.5: close call -- identify deciding criteria. Top leads by >0.5: recommend winner. If matrix contradicts intuition, ask which criterion is missing.
Append to active ADR session (.adr-session.json) or task plan.
5-persona parallel critique with consensus synthesis.
Extract or generate numbered proposals. Each: what it does, why it matters, how it differs from status quo (2-4 sentences). Research domain first if generating.
Load references/multi-persona-critique/personas.md. Build prompts for 5
personas, each receiving ALL proposals:
Each produces: STRONG/PROMISING/WEAK/REJECT per proposal, ranked list, cross-cutting observations.
Launch all 5 via Agent. Wait for ALL to complete.
Build consensus matrix (proposals x personas x ratings). Classify: CONSENSUS (4+ agree), CONTESTED (2-3 split), OUTLIER (1 vs 4). Score: STRONG=3, PROMISING=2, WEAK=1, REJECT=0. Sum per proposal (0-15).
Generate report using references/multi-persona-critique/synthesis-template.md:
consensus matrix, features to build, worth investigating, disagreements,
shelve, cross-cutting insights.
For roast-style code critique with HN personas and file:line validation, load
references/multi-persona-critique/roast.md.
Load on demand when the corresponding phase needs detailed lookup data.
| Context | Reference | Content |
|---|---|---|
| Codebase overview: language commands | references/codebase-overview/exploration-strategies.md | Per-language discovery commands |
| Codebase overview: report format | references/codebase-overview/report-template.md | 12-section report template |
| Codebase overview: deep-dive dispatch | references/codebase-overview/examples-and-errors.md | Parallel agent template, worked examples |
| Codebase overview: statistical lenses | references/codebase-overview/statistical-three-lenses.md | Three-lens statistical analysis |
| Codebase overview: metrics catalog | references/codebase-overview/statistical-metrics-catalog.md | 100-metric catalog |
| Codebase overview: statistical phases | references/codebase-overview/statistical-phase-details.md | Phase banners and workflows |
| Codebase overview: statistical examples | references/codebase-overview/statistical-analysis-examples.md | Real-world statistical workflows |
| Value analysis: implementation | references/repo-value-analysis/phase7-implement-template.md | Agent dispatch template |
| Health check: endpoint validation | references/service-health-check/endpoint-validator.md | Full endpoint validation methodology |
| Health check: security headers | references/service-health-check/security-headers.md | HSTS, CSP reference |
| Health check: endpoint config | references/service-health-check/endpoint-config-preferred-patterns.md | Config patterns |
| Health check: auth endpoints | references/service-health-check/auth-endpoint-patterns.md | Auth endpoint patterns |
| Health check: CVE sources | references/service-health-check/cve-source-check.md | CVE source check methodology |
| ADR: agent prompts | references/adr-consultation/agent-prompts.md | 3-agent prompt templates |
| ADR: artifact patterns | references/adr-consultation/consultation-patterns.md | Verdict display, artifact templates |
| ADR: failure modes | references/adr-consultation/consultation-preferred-patterns.md | Dispatch and verdict fixes |
| ADR: error recovery | references/adr-consultation/error-handling.md | Error recovery by phase |
| Decision: archetypes | references/decision-helper/decision-archetypes.md | Archetype-specific criteria weights |
| Decision: failure modes | references/decision-helper/decision-preferred-patterns.md | Scoring discipline patterns |
| Critique: personas | references/multi-persona-critique/personas.md | 5 persona specifications |
| Critique: synthesis | references/multi-persona-critique/synthesis-template.md | Consensus matrix and report |
| Critique: examples | references/multi-persona-critique/examples-and-errors.md | Worked examples, failure modes |
| Critique: roast mode | references/multi-persona-critique/roast.md | HN persona evidence-based critique |
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Manage multiple Claude Code accounts: add, list, check, launch, and install shell aliases for 10+ isolated CLAUDE_CONFIG_DIR profiles.
日本語の概要は準備中です。原文の説明を表示しています。
Improve architecture across modules by deepening interfaces.
日本語の概要は準備中です。原文の説明を表示しています。
Background memory consolidation — overnight review, merge, and injection payload for memory files.
日本語の概要は準備中です。原文の説明を表示しています。
Jev-driven browser automation: Jev picks operations, programs execute, a text model writes field values only when Jev cannot pick one from the goal.
日本語の概要は準備中です。原文の説明を表示しています。
Write, compose, integrate, and improve programs that call Jev, TypeSafe's System One judgment model.
日本語の概要は準備中です。原文の説明を表示しています。
Business operations: strategy, technology, growth, competitive intelligence, support, finance, HR, legal, operations, sales, productivity, product management.
日本語の概要は準備中です。原文の説明を表示しています。