po4yka/llm-wiki-skills/llm-wiki-news-radar

LLM-Wiki News Radar

Goal

Produce a current, source-cited ecosystem update for LLM-Wiki and adjacent technologies.

When to use

• The user asks about the latest, current, or recent state of LLM-Wiki, wiki memory, Agent Skills, RAG/GraphRAG, or related coding-agent knowledge tooling.
• The user asks "what changed" in these areas since a specific date or event.
• The user wants a source-cited digest of new releases, papers, tools, or standards before adopting them.
• Not for general questions that do not need freshness checking (use a vault-query skill instead).

Mandatory freshness rule

Always browse. Do not answer current-state questions from memory.

Use absolute dates in the answer, especially when the user says latest, recent, today, this week, this month or current.

Watch areas

Search across:

• LLM-Wiki / wiki memory / OpenWiki;
• LangChain, DeepAgents and related wiki-memory projects;
• Karpathy-style LLM-Wiki discussions;
• Agent Skills, skills.sh, Claude Code, Codex, Cursor, OpenCode;
• Obsidian/local-first knowledge workflows;
• qmd or local hybrid retrieval;
• RAG, GraphRAG, LightRAG, HippoRAG and agent-native retrieval;
• provenance, anti-slop, context poisoning, memory benchmarks;
• arXiv papers and benchmark releases;
• GitHub repos and release notes.

Inputs

• The topic or watch area(s) to focus the search on; defaults to the full watch-area list above.
• The time window to cover (last 7 days, last 30 days, last 90 days, since a known event, or general landscape); infer or ask if not given.
• Optional: an LLM-Wiki vault path, if the result should be saved via the file-back step.

Procedure

1. Set the time window

Infer or ask for the window:

• last 7 days;
• last 30 days;
• last 90 days;
• since a known event;
• general current landscape.

If no window is given, default to the last 90 days plus any major still-relevant baseline sources.

2. Search diverse sources

Use at least three source families when possible:

• official docs/blogs/release notes;
• GitHub repositories/releases/issues;
• papers/preprints;
• independent analysis or community discussions.

Prefer primary sources for technical claims.

3. Classify findings

Group updates by type:

4. Evaluate relevance

For each important item, answer:

• What changed?
• Why does it matter for LLM-Wiki users?
• Who should care: personal user, team, product builder, researcher?
• Does it change a previous recommendation?
• What needs verification before adoption?

5. Output

## Current as of YYYY-MM-DD
 
## Executive summary
 
## Major updates
 
## New or changed tools
 
## New papers / benchmarks
 
## Standards and agent ecosystem
 
## Risks and warnings
 
## What I would change in an LLM-Wiki setup now
 
## Sources checked

Output

A single Markdown digest following the section template above (Current as of / Executive summary / Major updates / New or changed tools / New papers / Standards / Risks / Sources checked), grouped by the classification types from step 3, with every current-state claim carrying an inline citation to the source that supports it. When run inside an LLM-Wiki vault, the digest may additionally be offered for file-back as described below.

Citation rules

• Cite every factual current-state claim.
• Do not cite a source for a claim it does not support.
• Do not group all citations at the end.
• Use primary sources for install commands, APIs, release status and licenses.

Optional file-back

If working inside an LLM-Wiki vault, offer to save the update as:

wiki/queries/YYYY-MM-DD-llm-wiki-news-radar.md

Mark it status: draft and stale_after within 30-90 days.

Safety gates

• Never state a current-state fact (release status, version, maintenance status, pricing) without having browsed and cited a source for it.
• Do not fabricate dates, version numbers, or adoption claims; mark anything unverified as such instead of guessing.
• File-back into the vault is optional and report-only until the user confirms; never overwrite an existing wiki page.
• Surface stale, unmaintained, or low-provenance projects under the risk category rather than recommending them silently.