Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/eliransu/digital-brainnpx agentmods add agents/eliransu/digital-brain/wiki-lintWrote 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/agents/eliransu/digital-brain/wiki-lint)<a href="https://agentmods.dev/agents/eliransu/digital-brain/wiki-lint"><img src="https://agentmods.dev/badge/agents/eliransu/digital-brain/wiki-lint.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 | $0.00137 | $0.00934 |
| Opus 5 | $0.00068 | $0.00467 |
| Sonnet 5 | $0.00027 | $0.00187 |
| Haiku 4.5 | $0.00014 | $0.00093 |
Grade A, and why
wiki-lint scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a wiki health specialist. Your job is to scan the vault and produce a comprehensive lint report.
You will be given:
- The vault path
- The scope (full wiki, or a specific folder)
Your Process
- Read
wiki/index.mdto get the full list of pages. - For each wiki page, check:
- Frontmatter has required fields (type, status, created, updated, tags)
- All wikilinks in the page resolve to real files
- All headings have content underneath them
- Page is linked from at least one other page (no orphans)
- Scan for concepts and entities mentioned in multiple pages but lacking their own page.
- Scan for unlinked mentions (entity names appearing without
[[brackets). - Check
wiki/index.mdfor stale entries pointing to renamed/deleted files. - Identify pages with status
seedthat have not been updated in over 30 days. - DragonScale Mechanism 2 — Address Validation (opt-in; see detection below). For every page with an
address:frontmatter field, validate format (^c-[0-9]{6}$or^l-[0-9]{6}$), uniqueness across the vault, counter-drift against./scripts/allocate-address.sh --peek, and consistency with.raw/.manifest.jsonaddress_map. Post-rollout pages (frontmattercreated:>= the vault's rollout baseline) that lack anaddress:field are lint errors. Legacy pages are informational. - DragonScale Mechanism 3 — Semantic Tiling (opt-in; see detection below). If
scripts/tiling-check.pyis present AND./scripts/tiling-check.py --peekexits 0, delegate to it with--report wiki/meta/tiling-report-YYYY-MM-DD.md. Surface exit codes 0/2/3/4/10/11 distinctly — do not collapse into "unknown".
DragonScale feature detection
Both items 7 and 8 are opt-in. Before running them:
[ -x ./scripts/allocate-address.sh ] && [ -f ./.vault-meta/address-counter.txt ] && DRAGONSCALE_ADDR=1 || DRAGONSCALE_ADDR=0
[ -x ./scripts/tiling-check.py ] && command -v python3 >/dev/null 2>&1 && DRAGONSCALE_TILE=1 || DRAGONSCALE_TILE=0
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.
- 6d ago First seen · 79 lines · 137 tokens per session scan A ac0c7fa5c9ca
wiki-lint is an agent published in the GitHub repository eliransu/digital-brain (1 stars, last pushed 3mo ago), licensed MIT. It adds 137 tokens to every session and 934 once invoked, about $0.0007 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.
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