Borrowing it
Nothing to install: this file belongs to arnaudgelas/K-Ops. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/arnaudgelas/K-Ops/main/.claude/skills/ingest-sources/SKILL.mdgit clone --depth 1 https://github.com/arnaudgelas/K-OpsWrote 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/arnaudgelas/k-ops/ingest-sources)<a href="https://agentmods.dev/skills/arnaudgelas/k-ops/ingest-sources"><img src="https://agentmods.dev/badge/skills/arnaudgelas/k-ops/ingest-sources/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/arnaudgelas/k-ops/ingest-sources"><img src="https://agentmods.dev/badge/skills/arnaudgelas/k-ops/ingest-sources.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 | $0.00023 | $0.01239 |
| Opus 5.5 | $0.00009 | $0.00496 |
| Sonnet 5.5 | $0.00005 | $0.00248 |
| Haiku 4.5 | $0.00002 | $0.00124 |
Grade A, and why
ingest-sources 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 1mo 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ingest Sources
Goal
Turn already-fetched raw source folders into structured source summary notes that the vault compiler can use.
Context
Mechanical fetching and normalization is handled by kops/ingest_sources.py via kb.py ingest.
This skill covers the agent-driven step that follows: reading normalized content and writing or updating source summaries.
Inputs
data/registry.json- registry of all ingested sourcesdata/raw/<id>/normalized.md- normalized text for each sourcedata/raw/<id>/metadata.json- source metadata (URL, type, timestamps)- Existing
notes/Sources/<id>.mdif a prior summary exists
Output contract
- Update only the source notes that need to change.
- Preserve provenance and uncertainty explicitly.
- Flag weak or incomplete captures instead of smoothing them over.
Required note shape
Frontmatter (all fields mandatory per config/schema.yaml):
source_id(canonicalsrc-[0-9a-f]{10})titlesource_urlsource_kind(must map to a canonical schema value):arxiv-paper|paper-pdf|github-repo-snapshot|github-file|official-doc|spec|blog|news|local-file|imported-model-report|citation-stubevidence_strength(must map to a canonical schema value):primary-doc|primary-doc-partial|official-spec|strong|code|maintainer-commentary|changelog|pr-issue|secondary|model-generated|stub|citation-only|image-onlysource_status(defaults toactive)ingested_at(ISO-8601 date, e.g. 2026-06-14T10:53:44Z)tags(must includekb/source)
Kind-Specific Required Frontmatter:
- arxiv-paper:
authors,arxiv_id,published_date,abstract - paper-pdf:
page_count - github-repo-snapshot:
git_commit,branch,tracked_file_count,sampled_file_count - github-file:
github_url,git_commit - official-doc:
organization - spec:
organization,version,status
Strong PDF / Imported Report Constraints:
- PDF Coverage: Any PDF source (
paper-pdf,arxiv-paper, or URL ending in.pdf) with strong evidence strength (primary-doc,strong,official-spec) MUST includeextraction_coveragemetadata in its frontmatter (e.g.extraction_coverage: 1.0). - Imported Report: If kind is
imported-model-report, setauthority: lead_only,verification_state: needs_primary_sources,evidence_strength: secondary. - Imported Citation Stub: If kind is
citation-stub, setcanonical_url: "<url>",authority: lead_only,verification_state: needs_fetch,evidence_strength: stub.
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.
- 1mo ago First seen · 91 lines · 23 tokens per session scan A f50bc8409a13
ingest-sources is a skill published in the GitHub repository arnaudgelas/K-Ops (1 stars, last pushed 2mo ago), licensed MIT. It adds 23 tokens to every session and 1,239 once invoked, about $0.0001 per session on Opus 5.5. 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
kb-lint
Health check for the PARA Knowledge Base. Detects orphan documents, broken links, index drift, tag issues, and stale content. Run periodically or as part of weekly review.
kb-index
Update Knowledge Base indexes. Smart mode detects changes and updates only what's needed. Full rebuild available with --full flag. Use after adding/moving documents or when indexes feel stale.
wiki-ingest
Ingest exactly one research paper or source document into an open-llm-wiki vault. Use when the user explicitly asks to add, ingest, process, or publish a paper into the wiki. The workflow parses the source, drafts a source page, runs independent QA, publishes only after the quality gate passes, extracts and normalizes…
query-writeback
Answer cross-source questions about an open-llm-wiki vault and optionally write reusable synthesis back into concept pages. Use when the user asks a wiki question that requires comparing, connecting, or tracing multiple source/concept pages. By default answer first and propose writeback; modify files only when the…
wiki-lint
Run a health check for an open-llm-wiki vault. Use when the user asks to lint, audit, validate, or periodically check wiki quality. The default mode is report-only: inspect schema compliance, QA coverage, links, stale claims, contradictions, and log health. Modify files only when the user explicitly requests fix mode…
llm-wiki
Explain and apply the foundational LLM Wiki architecture and knowledge-management strategy. Use for setup, architecture, schema, or organization decisions; operational ingest/query/lint work uses dedicated skills.