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- rlaope/bestwork-agent
- 최근 소스 활동
- 2026년 4월 3일 03:12
- 감지된 SKILL.md 언어
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설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/rlaope/bestwork-agent --skill plan명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Evidence-driven causal tracing — competing hypotheses, falsification, rebuttal round, recommended next probes
Feature validation gate — research, define purpose, stress-test from real user perspective before building
Maximum parallelism burst — all tasks execute simultaneously with no coordination overhead
SOC 직업 분류 기준
SKILL.md 표시 중
| name | plan |
| description | Analyze task scope and recommend a bestwork team composition before executing |
When this skill is invoked, IMMEDIATELY print:
[BW] analyzing scope...
The user's request follows after the skill invocation. Analyze it thoroughly before doing anything.
Gather concrete data about what the task requires. Do ALL of the following:
Identify affected files — based on the user's request, determine which files will need to be created, modified, or deleted. Use git ls-files, find, and your knowledge of the codebase to list them. Count them.
Identify domains — classify each file into a domain:
Estimate complexity — score 1-5 based on:
Based on the analysis, recommend ONE team mode:
Conditions: 1-2 files, single domain, complexity 1-2.
Pick the best-fit specialist from:
Print:
[BW] plan: SOLO
scope: {N} files, {domain}
complexity: {score}/5
agent: {specialist}
tasks:
1. {what will be done}
2. {what will be done}
confirm? (y/n)
Conditions: 3-5 files, 2 domains, complexity 2-3.
Pick 2 complementary specialists. Common combos:
Print:
[BW] plan: PAIR
scope: {N} files across {domains}
complexity: {score}/5
agents: {specialist1} + {specialist2}
tasks:
1. [{agent}] {what will be done}
2. [{agent}] {what will be done}
confirm? (y/n)
Conditions: 5-10 files, 3+ domains, complexity 3-4, or any task benefiting from quality gates.
Pick the best-fit trio from all 49 specialists:
Print:
[BW] plan: TRIO
scope: {N} files across {domains}
complexity: {score}/5
agents:
tech: {tech-specialist} — implements
pm: {pm-specialist} — verifies requirements
critic: {critic-specialist} — reviews quality
execution:
1. [{tech}] {implementation task}
2. [{pm}] verify: {what PM checks}
3. [{critic}] review: {what critic checks}
(max 3 feedback rounds if rejected)
confirm? (y/n)
Conditions: 10+ files, 4+ domains, complexity 4-5, feature work.
Pick a squad preset or custom composition:
Print:
[BW] plan: SQUAD
scope: {N} files across {domains}
complexity: {score}/5
squad: {preset or "custom"}
- {specialist1} ({role})
- {specialist2} ({role})
- {specialist3} ({role})
- {specialist4} ({role})
execution (parallel):
1. [{agent1}] {task}
2. [{agent2}] {task}
3. [{agent3}] {task}
4. [{agent4}] {task}
resolution: majority vote on disagreements
confirm? (y/n)
Conditions: 10+ files, architecture changes, complexity 5, refactoring, or security-critical.
Pick a hierarchy preset:
Print:
[BW] plan: HIERARCHY
scope: {N} files, architecture-level
complexity: {score}/5
chain: {preset}
4. {C-level} — final approval
3. {Lead} — architecture review
2. {Senior} — implementation review
1. {Junior} — implementation
execution (bottom-up, review top-down):
1. [{junior}] implement: {task}
2. [{senior}] review + improve
3. [{lead}] architecture check
4. [{c-level}] final decision
confirm? (y/n)
Wait for user input. Accept:
[BW] plan cancelled.Before execution, ALWAYS save the plan to disk:
mkdir -p .bestwork/plans
Write the plan as JSON to .bestwork/plans/<timestamp>-<slug>.json:
{
"created": "<ISO timestamp>",
"task": "<user's original request>",
"mode": "solo|pair|trio|squad|hierarchy",
"scope": { "files": ["..."], "domains": ["..."], "complexity": N },
"agents": [{ "name": "tech-backend", "role": "tech", "tasks": ["..."] }],
"status": "pending|executing|complete|cancelled"
}
Also write a human-readable summary to .bestwork/plans/<timestamp>-<slug>.md.
This enables:
./plan --last — re-load and resume the most recent plan./plan --list — list all saved plansWhen the user says ./plan --last:
.json file from .bestwork/plans/Once confirmed, update the saved plan's status to "executing". Then route to the appropriate team mode. Print:
[BW] executing plan...
Then execute based on the confirmed mode:
SOLO: Load the specialist's prompt from prompts/tech/{name}.md (or the matching category). Execute the task directly using that agent's expertise and perspective.
PAIR: Execute sequentially — first specialist handles their domain files, second specialist handles theirs. Cross-review at the end.
TRIO: Execute as ./trio — spawn Tech agent (implement), PM agent (verify), Critic agent (review). Feedback loop up to 3 rounds. Record to meeting log at .bestwork/state/meeting.jsonl.
SQUAD: Spawn all agents in parallel using run_in_background. Each agent works on their assigned files. Disagreements resolved by majority vote. Record to meeting log.
HIERARCHY: Execute bottom-up (Junior implements first), review top-down (C-level approves last). Each level can send work back down with feedback. Record to meeting log.
For trio/squad/hierarchy, write the meeting log:
mkdir -p ~/.bestwork/state && echo '{"type":"header","teamName":"plan","mode":"<MODE>","task":"<TASK>","classification":"PLAN","developerCount":<N>,"routingReason":"plan skill recommendation"}' > .bestwork/state/meeting.jsonl
After execution completes, update the saved plan's status to "complete" and print:
[BW] plan complete. mode={MODE}, agents={N}, files={N}.
saved: .bestwork/plans/<filename>.md