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 po4yka/llm-wiki-skills --skill llm-wiki-ingestion-stackgit clone --depth 1 https://github.com/po4yka/llm-wiki-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/po4yka/llm-wiki-skills/llm-wiki-ingestion-stack)<a href="https://agentmods.dev/skills/po4yka/llm-wiki-skills/llm-wiki-ingestion-stack"><img src="https://agentmods.dev/badge/skills/po4yka/llm-wiki-skills/llm-wiki-ingestion-stack/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/po4yka/llm-wiki-skills/llm-wiki-ingestion-stack"><img src="https://agentmods.dev/badge/skills/po4yka/llm-wiki-skills/llm-wiki-ingestion-stack.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 | $0.00068 | $0.02254 |
| Opus 5 | $0.00034 | $0.01127 |
| Sonnet 5 | $0.00014 | $0.00451 |
| Haiku 4.5 | $0.00007 | $0.00225 |
Grade A, and why
llm-wiki-ingestion-stack 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.
How it starts
The opening of the file, as written. The whole thing — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LLM-Wiki Ingestion Stack
Goal
Turn messy source material into preserved raw sources, normalized manifests, evaluated extraction artifacts and reviewable wiki drafts without losing provenance or trusting generated summaries as evidence.
Use references/docs/20-ingestion-pipelines.md as the reference architecture for source taxonomy, pipeline archetypes, tool choices, manifests, chunk schemas, quality gates, sync/dedupe and rollout. Use references/templates/source-manifest.yaml as the canonical source manifest shape; do not recreate a partial manifest schema in prose.
When to use
- A batch of PDFs, Office files, scanned documents, web clips, audio/video, code repos, chats/emails or database tables needs to become source-preserving Markdown for the wiki.
- You need a source manifest, provenance/anchor schema, or chunking scheme before any extraction work starts.
- An existing ingestion path is producing empty extractions, table loss, OCR gibberish, orphaned attachments or missing provenance anchors.
- You are deciding incremental sync/dedupe rules or an automation mode (manual batch, watched inbox, PR-based ingest, queue/worker ETL, connector platform).
- You need a golden corpus and ingestion eval plan before wiring CI gates in
llm-wiki-eval-tooling.
Inputs
- Source types and volume.
- Local-only or cloud-allowed policy.
- Existing folders:
inbox/,raw/,wiki/,indexes/,evals/. - Target output: only manifests, source pages, entity pages, concept pages, synthesis pages, indexes or exports.
- OCR, layout, table, formula, image, audio/video, email/chat, code, tabular and web-capture needs.
- Model/provider/data policy.
- Security and privacy constraints.
- Desired automation mode: manual batch, watched inbox, PR-based ingest, queue/worker ETL, connector platform.
Procedure
1. Classify source material
Use this taxonomy:
| Source type | Canonical capture unit | Main risk |
|---|---|---|
| PDF / Office / HTML documents | file or URL | reading-order, table and layout loss. |
| Scanned documents | scanned PDF or image | OCR errors and missing text layer. |
| Web pages | rendered page snapshot | JS-rendered content loss and link rot. |
| Audio/video | media file or stream | transcription drift and missing timestamps. |
| Code repositories | repo / commit / file tree | syntactic flattening and stale docs. |
| Chats/emails | thread / message / attachment | thread breakup, attachment loss and privacy risk. |
| Databases/tables | table / query / partition | schema drift and row-level provenance loss. |
| Images/figures | image / figure / page region | context loss and weak captions. |
What ships with it
2 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.
- 11d ago First seen · 271 lines · 68 tokens per session scan A 91cd607c5ff4
llm-wiki-ingestion-stack is a skill published in the GitHub repository po4yka/llm-wiki-skills (3 stars, last pushed 18d ago), licensed MIT. It adds 68 tokens to every session and 2,254 once invoked, about $0.0003 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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