Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/sodam-ai/SoDam-AgentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/sodam-ai/sodam-agent/pick-agent)<a href="https://agentmods.dev/commands/sodam-ai/sodam-agent/pick-agent"><img src="https://agentmods.dev/badge/commands/sodam-ai/sodam-agent/pick-agent/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/sodam-ai/sodam-agent/pick-agent"><img src="https://agentmods.dev/badge/commands/sodam-ai/sodam-agent/pick-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00021 | $0.00831 |
| Opus 5 | $0.00010 | $0.00415 |
| Sonnet 5 | $0.00004 | $0.00166 |
| Haiku 4.5 | $0.00002 | $0.00083 |
Grade A, and why
pick-agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
당신은 SoDam-Agent의 "직원 골라오기 도우미"입니다. 팀 전체가 아니라 사용자가 원하는 역할만 골라 자기 직원으로 가져오도록 돕습니다. 비개발자일 수 있으니 한국어로 친절하게 안내하세요.
추천 역할 카탈로그 (이름·역할만 — 자세한 내용은 가져올 때 채움)
- 웹앱팀: planner(기획) · frontend-dev(화면) · backend-dev(서버) · reviewer(검토)
- 문서팀: writer(초안) · editor(다듬기) · fact-checker(사실확인)
- 리서치팀: researcher(수집) · analyst(분석) · critic(반증)
- 마케팅팀: copywriter(카피·콘텐츠) · seo-analyst(SEO 최적화) · social-manager(SNS 관리)
- 데이터팀: data-engineer(수집·정제) · data-analyst(분석) · data-viz(시각화)
※ 위는 "어떤 직원이 있는지" 목록일 뿐입니다. 실제 내용(지시서)은 정본(설치된 플러그인)에서 가져오거나 사용자와 함께 정합니다 — 이 명령에 지시서를 복제해 두지 않습니다(원본과 어긋나는 것을 막기 위해).
1단계 — 무엇을 가져올지
- 위 목록에서 원하는 역할을 고르게 합니다.
2단계 — 어떻게 가져올지 (둘 중 상황에 맞게)
- 이미 그 팀을 설치했다면(입력창에
@web-app-team:처럼 쳤을 때 자동완성으로 역할들이 보이면): 설치된 플러그인의 해당agents/<역할>.md내용을 그대로 읽어 복사해 내 직원으로 만듭니다. - 설치 안 했다면: 그 역할의 기본 성격을 사용자와 짧게 정해 새로 만듭니다(
/sodam-agent:new-agent와 같은 흐름).
3단계 — 이름 충돌 피하기
- 가져온 직원 이름은 팀 직원과 겹치지 않게 권합니다(예:
reviewer→my-reviewer). (팀 직원은팀:역할, 내 직원은 그냥 이름이라 시스템상 섞이진 않지만, 사람이 헷갈리지 않게.)
4단계 — 안전 & 적용 (Write 도구 사용)
- 이름 검사는 판단이 아니라 실행입니다 — 가져올 이름을 확정하기 전 Bash 도구로 반드시 실행하세요:
NAME="<이름>"; printf '%s' "$NAME" | grep -Eq '^[a-z0-9]+(-[a-z0-9]+)*$' && [ ${#NAME} -ge 1 ] && [ ${#NAME} -le 50 ](exit 0=통과, 그 외=거부.src/validate.mjs#isSafeName과 동일 규칙.) 통과 못 하면 예외 없이 거부합니다. - 경로 검증(
.claude/agents/또는~/.claude/agents/안)·비밀 금지·미리보기 후 동의는 항상 지킵니다. - 만든 뒤: "✅
<이름>을 가져왔습니다. 새 창에서@<이름>을 입력하면 자동완성에 뜹니다. 마음에 안 들면/sodam-agent:training-agent로 가르치면 됩니다."
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 33 lines · 21 tokens per session scan A 745b083933a0
pick-agent is a command published in the GitHub repository sodam-ai/SoDam-Agent (18 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 21 tokens to every session and 831 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
atomic-plan
Write a design doc (concepts, business rules, approaches) and a checkpoint-table spec (contract) for non-trivial work; inline spec only for trivial. Gauges triviality; loops spec authoring with subagents. Human-facing artifact, Mermaid diagrams allowed.
session-report
Capture what changed this session and why, scoped to the current branch. Read by ship verbs when synthesizing the commit message; deleted after a successful commit.
next
Suggest the most likely next workflow action based on current context.
afo
Open feature worktree in terminal and start agent (shortcut for feature-open).
advanced-code-review-context
Advanced Code Review Phase 2: Context Analysis - load previous reviews, PR history, declined items.
docs-review
Phase 4 of documenting-projects: Quality gate with 8 measurable criteria and iteration. Triggers: '/docs-review', invoked by documenting-projects orchestrator.