agentsclimarketplace

Query

Skill lokesh-go/llm-wiki/.claude/skills/query

A personal, compounding tech knowledge base maintained by an LLMFrom the repository description

Install
npx -y skills add lokesh-go/llm-wiki --skill query

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

4.2 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it

Skill: /query

Trigger

User types: /query <question>

STRICT RULE

NEVER read from raw/ during /query. raw/ is the source archive — only /compile reads it. wiki/ is the LLM-readable knowledge base — /query ALWAYS reads from wiki/ only. If a topic has not been compiled into wiki/ yet, say so and suggest running /ingest.


Step 1 — ROUTE (read vocabs/index.md)

  1. Read the FULL vocabs/index.md file (~200 tokens)
  2. From the question, identify which vocab categories are relevant Example: "When should I use Redis vs Kafka?" → matches categories: technologies, data-storage, system-design
  3. Note the canonical term names from those categories (these are the tags you will match against in Step 2)

Step 2 — FILTER (read wiki/index.md)

  1. Read wiki/index.md
  2. Scan EVERY section for entries whose tags overlap with Step 1 terms:
    • Concepts

    • Entities

    • Patterns

    • Best Practices

    • Comparisons

    • Sources

    • Saved Queries ← DO NOT SKIP THIS SECTION

  3. From all matching entries across all sections, select top 3-7 candidates ranked by how many tags overlap with the question's terms

Priority Rule for Saved Queries:

If a "## Saved Queries" entry has tags that match the question: → ALWAYS include that page as a candidate, ranked FIRST → A saved query was compiled specifically to answer a question like this → It will likely satisfy the query with far fewer tokens than reading raw pages


Step 3 — READ (open only matched pages)

For each candidate page (starting from top-ranked):

  1. Open the page

  2. Read ONLY the > blockquote summary line (first line after frontmatter):

    • If summary directly answers or closely matches the question: → Read the full page → If this is a Saved Query page AND the answer is sufficient: STOP here. Do not open remaining candidates. Go to Step 4.
    • If summary does not match: → Skip this page, move to next candidate
  3. Continue until you have 2-5 pages with confirmed relevant content

Short-circuit rule:

If a Saved Query page fully answers the question → skip all remaining candidates. No need to re-read the underlying concept/entity pages. This is the token-saving payoff of saved queries.


Step 4 — ANSWER

  • Synthesize a clear answer from the pages read
  • Cite pages inline: [[page-name]]
  • If answer came primarily from a Saved Query page, note that: "Answer sourced from saved query [[page-slug]]"
  • State confidence: high | medium | low
  • State which pages were consulted and how many tokens were saved vs. reading from scratch (estimate: "read 1 saved query vs ~5 pages")

Step 5 — SAVE DECISION

Ask the user: "Worth saving to wiki? (y/n)"

If no → stop.

If yes → do ALL of the following:

5a — Write the Query Page

File: wiki/queries/<slugified-question>.md Template from wiki/CLAUDE.md (Query Page template): Frontmatter: t: query cat: <most relevant vocab category from Step 1> tags: [<canonical vocab terms used in the answer>] src: 0 rel: [<all pages consulted in Step 3>] upd: <today YYYY-MM-DD> Opening line: > Answer to: "<exact question asked>" Sections: ## Answer ← full synthesized answer with [[citations]] ## Pages Consulted ← [[page1]], [[page2]] as wikilinks (for graph edges) ## Confidence ← high | medium | low ## Follow-up Questions ← related questions worth exploring

5b — Update wiki/index.md

Under "## Saved Queries" section, add:

  • [[<slug>]] | query | tag1,tag2,tag3 | 0 (tags must match canonical vocab terms so future queries can find this) Update frontmatter:
  • Increment pages: count by 1
  • Update upd: to today's date

5c — Update wiki/log.md

Append:

[YYYY-MM-DD] query | <original question>

<one line: key answer or decision captured>

5d — Backlink from Consulted Pages (prevents orphan in graph)

For each wiki page read in Step 3:

  • Open the page
  • Under its "## Sources" section add:
    • [[<query-slug>]]: referenced in query "<question>"
  • Increment its src: frontmatter count by 1

This ensures the saved query page is connected in the Obsidian graph and will NOT be flagged as an orphan by /lint.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 326,851. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.