Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add quantsquirrel/claude-forge-smith/plugin install forgeWrote 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/skills/quantsquirrel/claude-forge-smith/forge)<a href="https://agentmods.dev/skills/quantsquirrel/claude-forge-smith/forge"><img src="https://agentmods.dev/badge/skills/quantsquirrel/claude-forge-smith/forge.svg" alt="Measured on agentmods" 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 | $0.00037 | $0.03425 |
| Opus 5 | $0.00018 | $0.01713 |
| Sonnet 5 | $0.00007 | $0.00685 |
| Haiku 4.5 | $0.00004 | $0.00343 |
Grade A, and why
forge scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 429 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Forge Skill
Systematically improve a skill through test-driven evaluation and statistical validation.
REQUIRED BACKGROUND: First invoke forge:smelt skill for TDD methodology applied to skills. See testing-skills-with-subagents.md in that skill's directory for pressure scenario templates.
Quick Reference
| Step | Action |
|---|---|
| 1 | Trial Branch 생성 |
| 2 | 스킬 찾기 및 읽기 |
| 3 | Pressure Scenario 생성 |
| 4 | 기준선 평가 (3회) - evaluator 사용 |
| 5 | Discoverability 평가 (CSO 체크) |
| 6 | 개선 사항 식별 |
| 7 | 개선 적용 (GREEN Phase) |
| 8 | 개선 후 평가 (3회) |
| 9 | 신뢰구간 분리 확인 |
| 10 | Trial Branch 결과 처리 (병합/폐기) |
| 11 | Stats 업데이트 (upgraded: true) |
Upgrade Mode Selection
스킬 업그레이드 시작 전, 적합한 모드를 자동 선택합니다.
Mode Decision Flow
스킬 분석 (get_upgrade_mode 호출)
│
├─ "TDD_FIT" ──→ TDD Mode (기존 워크플로우)
│ - Trial Branch
│ - 3x 평가 + 95% CI (또는 n=5 고정밀)
│ - 통계적 검증
│
└─ "HEURISTIC" ──→ Heuristic Mode (신규)
- Usage 데이터 분석
- 구조 품질 평가
- 자동 개선 제안
Mode Detection
업그레이드 시작 시 다음 bash 함수를 호출하여 모드 결정:
source "${CLAUDE_PLUGIN_ROOT}/hooks/lib/storage-local.sh"
MODE=$(get_upgrade_mode "$skill_name")
TDD Mode Options
| Option | Sample Size | CI Width | When to Use |
|---|---|---|---|
| Standard | n=3 | Wider | 빠른 피드백, 대부분의 경우 |
| High Precision | n=5 | Narrower | 미묘한 개선 검증, 중요한 스킬 |
사용자가 /forge --precision=high 또는 /forge -n5로 n=5 모드 선택 가능
TDD Mode (기존)
- 조건: 테스트 파일 또는 pressure-scenarios.md 존재
- 검증:
check_skill_has_test()→ true - 워크플로우: Step 1-11 (기존 그대로)
Heuristic Mode (신규)
- 조건: 테스트 파일 없음
- 검증:
get_upgrade_mode()→ "HEURISTIC" - 워크플로우:
- Usage 데이터 로드 (
get_all_skills_summary()) - 서브에이전트 호출:
Task(subagent_type="forge:heuristic-evaluator", prompt="Evaluate skill: <skill-name>") - 점수 60 미만 → 자동 개선 제안 적용
- Trial Branch에서 개선 적용
- 1주일 후 사용량 변화로 검증 (
get_usage_trend())
- Usage 데이터 로드 (
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 429 lines · 0 tokens per session scan A 79c7e225ae35
forge is a skill published in the GitHub repository quantsquirrel/claude-forge-smith (2 stars, last pushed 6mo ago), licensed MIT. It adds 37 tokens to every session and 3,425 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
testing-agents-with-subagents
Test agents via subagents: known inputs, captured outputs, verification.
tdd
TDD with red-green-refactor loop and vertical slices. Triggers: TDD, test-first, red-green-refactor, test driving development.
triage-issue
Bug triage: explores codebase for root cause, files GitHub issue with TDD fix plan. Triggers: triage, investigate bug, fix plan, root cause, file issue, bug report.
test-driven-development
RED-GREEN-REFACTOR cycle with strict phase gates for TDD.
specify-incremental
Decompose a single-feature specification into a linear, phase-by-phase implementation plan. Use this for medium-complexity work — single feature, one or two components — where transparent human-in-the-loop phase review is preferred over factory automation.
ai-observability-promptfoo
Testing and evaluation framework for LLM prompts and applications -- promptfooconfig.yaml, assertions, model-graded evals, red teaming, CI/CD integration, custom providers, and comparative evaluation.