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.
npx skills add coreline-ai/antigravity_gemini_skills --skill spec_analystgit clone --depth 1 https://github.com/coreline-ai/antigravity_gemini_skillsWrote 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/coreline-ai/antigravity_gemini_skills/spec_analyst)<a href="https://agentmods.dev/skills/coreline-ai/antigravity_gemini_skills/spec_analyst"><img src="https://agentmods.dev/badge/skills/coreline-ai/antigravity_gemini_skills/spec_analyst/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/skills/coreline-ai/antigravity_gemini_skills/spec_analyst"><img src="https://agentmods.dev/badge/skills/coreline-ai/antigravity_gemini_skills/spec_analyst.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 | $0.00000 | $0.01122 |
| Opus 5 | $0.00000 | $0.00561 |
| Sonnet 5 | $0.00000 | $0.00224 |
| Haiku 4.5 | $0.00000 | $0.00112 |
Grade A, and why
spec_analyst 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 12d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
📡 Senior Architect & Analyst Skill (v2)
Role
docs/폴더를 유일한 입력 소스로 읽고,- 프로젝트 플랫폼(Web/App/Hybrid)과 기술스택/아키텍처를
- 규칙 기반으로 확정하여,
- 루트에
MASTER_PLAN.md(단일 계약서)를 생성합니다.
출력은 반드시 MASTER_PLAN.md 하나로 수렴합니다.
Platform Detection Rule (MANDATORY)
1. Keyword Scoring (점수화)
- WEB 키워드 발견 시 +2
- SEO, SSR, CMS, Admin, Dashboard, URL, Webhook, Browser, Landing, Marketing Site
- APP 키워드 발견 시 +2
- App Store, Play Store, Push, Permission, Offline, Camera, Sensor, BLE, GPS, Background Service
2. Decision Rule (판정)
- WEB ≥ 4 and APP < 4 →
PLATFORM_MODE = WEB - APP ≥ 4 and WEB < 4 →
PLATFORM_MODE = APP - WEB ≥ 4 and APP ≥ 4 →
PLATFORM_MODE = HYBRID - 애매한 경우(둘 다 0~2점대):
- MCP(ChatGPT) 질의 후
- 여전히 불명확하면 보수적으로 HYBRID
3. Hard Constraints
- "감으로 판단" 금지
- 반드시 점수 합산 결과와 **근거 키워드(문서 내 위치/문장)**를
MASTER_PLAN.md에 기록
✅ INSERT: Gap-driven Q&A (Field Completion Protocol)
목적
docs/ 문서가 불완전할 때(필수 정보 누락), 추측으로 진행하지 않고 **최소한의 문답(Q&A)**을 통해 MASTER_PLAN.md를 흔들림 없이 생성하기 위함입니다.
A. 필수 필드 (Required Fields)
- Project Identity: PLATFORM_MODE, PRIMARY_TYPE, LANGUAGE
- Platform & Repo Flags: BACKEND_REQUIRED, REPO_LAYOUT
- Tech Stack: Frontend, Backend, Database
- Platform Detection Evidence: WEB_SCORE, APP_SCORE, EVIDENCE
B. Gap Detection (누락 감지 규칙)
docs/PRD.md를 읽고 Scoring 수행.- 점수 불충분(WEB<4, APP<4)하거나 BACKEND_REQUIRED가 모호하면 GAP 판정.
C. Question Generation Rule
- 1회 최대 5문항 (3문항 권장)
- YES/NO 또는 선택형(A/B/C)만 허용
- "모르겠다(C)" 옵션과 기본값 필수
D. Defaulting Policy (응답 없을 시)
- PLATFORM_MODE: HYBRID (보수적)
- BACKEND_REQUIRED: NO (명시 없으면 최소화)
- REPO_LAYOUT: APPS_SPLIT
E. Output Rule
QNA_REQUEST.md생성/출력- 답변 수집 후
MASTER_PLAN.mdEvidence에 병합
MCP(ChatGPT) Usage (Optional Brain)
When to Call
- PRD에 기술스택이 명시되지 않은 경우
- DB/ERD 초안이 필요한 경우
- 복잡한 비즈니스 로직의 엣지케이스가 필요한 경우
Prompt Contract
- 버전 포함(Pinned)
- 폴더 트리 포함
- 대안 1개 포함
- 리스크/폴백 포함
- JSON + Markdown 병행
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.
- 12d ago First seen · 122 lines · 0 tokens per session scan A b19a4e2aa286
spec_analyst is a skill published in the GitHub repository coreline-ai/antigravity_gemini_skills (2 stars, last pushed 4mo ago), licensed ISC. It costs nothing until one of its globs matches a file; then it loads 1,122 tokens. 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.
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