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-WikiMateWrote 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-wikimate/wikimate-lint)<a href="https://agentmods.dev/commands/sodam-ai/sodam-wikimate/wikimate-lint"><img src="https://agentmods.dev/badge/commands/sodam-ai/sodam-wikimate/wikimate-lint/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-wikimate/wikimate-lint"><img src="https://agentmods.dev/badge/commands/sodam-ai/sodam-wikimate/wikimate-lint.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 | $0.00039 | $0.00236 |
| Opus 5 | $0.00019 | $0.00118 |
| Sonnet 5 | $0.00008 | $0.00047 |
| Haiku 4.5 | $0.00004 | $0.00024 |
Grade A, and why
wikimate-lint 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 11d 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
사용자의 옵시디언 볼트를 건강검진한다. "Wikimate Lint" 스킬의 워크플로우를 따른다:
- 볼트 확정(이름 또는 경로). 모르면 질문한다.
wikimate_lint도구를 호출해 구조적 문제를 스캔한다(★읽기 전용 — 수정·삭제·생성 안 함).- (노션 도구가 있으면) 도구가 돌려준
basenames로 노션 끊긴 색인을 대조한다. - 사람친화 보고. 0건이면 "깨끗해요"로 끝낸다.
- 고칠 게 있으면 AskUserQuestion 승인 게이트로만 제안한다(자동 수정 금지, 비가역은 개별 확인).
인자가 있으면 그 볼트를 대상으로 시작한다: $ARGUMENTS
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.
- 11d ago First seen · 15 lines · 39 tokens per session scan A 14500c80ab6f
wikimate-lint is a command published in the GitHub repository sodam-ai/SoDam-WikiMate (50 stars, last pushed today), licensed Apache-2.0. It adds 39 tokens to every session and 236 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 2026-08-30.
Other commands, from other repositories
lint
Run comprehensive wiki health check — orphans, broken links, contradictions, stale pages, index sync, MOC coverage, v2/v4/v5 frontmatter coverage, Core Context freshness, and cross-vault link integrity (mainVaultRelated/mainVaultCmds).
doctor
Runs diagnostic checks against a Vendure project and prints an actionable report. Use it for broken projects, upgrade verification, new-machine setup, or CI guard rails.
wiki-lint
Run a health check on the wiki. Invoke with /wiki-lint or "lint the wiki".
diagnostic
Command "diagnostic" from datacore-one/datacore, covering diagnostic, command context, when to reference dip-0002, quick reference and agents this command invokes.
ingest
Process files from inbox folders or external sources into Datacore with deep knowledge extraction.
refactor
Reorganize notes and folders safely — rename, move, split, merge — and rewire every affected wikilink.