Agent skill

Quick Search

by Abilityai in Abilityai/cornelius

Fast knowledge base retrieval - single FAISS search + graph connections, no subagents or LLM orchestration

MITAuto-check: notesKnowledge Management

Install Quick Search

skills CLI
$ npx skills add Abilityai/cornelius --skill quick-search -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Abilityai/cornelius quick-search --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Abilityai/cornelius.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/quick-search .claude/skills/quick-search && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
quick-search
GitHub stars
109
Token cost
~465 tokens
SKILL.md length
134 words
Files
1
Skills in repo
56
Repo updated
First seen
Licence
MIT

At a glance

Fast knowledge base retrieval - single FAISS search + graph connections, no subagents or LLM orchestration

  • Tasks that involve Vector databases
  • SKILL.md covers Purpose, Query, Process and Output Format, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Tasks that involve Subagents

What it does

Quick Search is an agent skill from Abilityai/cornelius. Fast knowledge base retrieval - single FAISS search + graph connections, no subagents or LLM orchestration

Its SKILL.md is about 470 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Knowledge Management, covering Vector databases, Subagents and Knowledge bases. The repository describes itself as: AI-powered second brain template for Claude Code + Obsidian. The licence is MIT.

When your agent uses it

  • Tasks that involve Vector databases
  • Tasks that involve Subagents
  • Tasks that involve Knowledge bases

Example prompts

  • “/quick-search”

Requirements

  • Pre-approved tools (allowed-tools): Bash, Read

What it can do on your machine

Read from SKILL.md and the folder at commit fd5e9a4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash
    • Read

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Quick Search loads about 465 tokens when it runs. Until then it costs about 30 tokens; SKILL.md has 134 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~30
When it runs · the whole SKILL.md, loaded when a task matches
~465

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash, Read

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Abilityai/cornelius at commit fd5e9a4, republished under its MIT licence (© Abilityai). 134 words, ~465 tokens.

Download SKILL.mdSave it as .claude/skills/quick-search/SKILL.md (or your agent's skills folder).
name
quick-search
description
Fast knowledge base retrieval - single FAISS search + graph connections, no subagents or LLM orchestration
allowed-tools
Bash, Read
argument-hint
<search query>
user-invocable
true

Fastest possible knowledge base retrieval. No subagents, no multi-layer orchestration, no changelogs.

Purpose

Return relevant notes and their graph neighborhood in minimal tool calls. Designed for speed over thoroughness.

Query

$ARGUMENTS

Process

Execute these two commands in parallel (single message, two Bash calls):

bash
# 1. Semantic search (6-14s - the unavoidable cost)
resources/local-brain-search/run_search.sh "$ARGUMENTS" --limit 5 --json

# 2. Graph connections for likely top hit (0.3s - nearly free)
resources/local-brain-search/run_connections.sh "$ARGUMENTS" --json

Then read the top result file using Read tool.

That's it. Three tool calls. Present results and stop.

Output Format

Keep it brief:

## [Query]

**Top matches:**
1. [[Note Title]] (0.XX) - [one-line summary from content]
2. [[Note Title]] (0.XX) - [one-line summary]
3. [[Note Title]] (0.XX) - [one-line summary]

**Graph neighborhood** (for top hit):
- Outgoing: [[Note]], [[Note]], ...
- Incoming: [[Note]], [[Note]], ...

**Top result content:**
[First ~30 lines of the highest-scoring note]

Rules

  • NO subagent spawning - do everything inline
  • NO changelog creation - this is a read-only lookup
  • NO multi-layer expansion - one search, one connection call, done
  • NO spreading activation - use static mode (faster for simple lookups)
  • Parallel execution - run search and connections in the same message
  • Maximum 3 tool calls - search + connections + read top file
  • If the user wants deeper analysis, tell them to use /recall or /find-connections

© Abilityai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/quick-search of Abilityai/cornelius.

Open the folder on GitHubat commit fd5e9a4

Compare with similar skills

Quick Search next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Quick Search compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Quick Search this skillAbilityai/cornelius109—~465Automated safety check: NotesMIT
Logseq Review Workflowlogseq/logseq45k—~3.8kAutomated safety check: PassAGPL-3.0
Remembercommercetools/ui-kit154—~2kAutomated safety check: NotesMIT
Knowledge Opsaffaan-m/ECC274k2 repos~1.7kAutomated safety check: PassMIT
Skill Developmentletta-ai/skills147—~941Automated safety check: PassMIT
Work Operating ModelNateBJones-Projects/OB14.7k—~2.2kAutomated safety check: PassCustom licence

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Questions about Quick Search

What does Quick Search do?

Fast knowledge base retrieval - single FAISS search + graph connections, no subagents or LLM orchestration. Quick Search is an agent skill from Abilityai/cornelius.

When should I use Quick Search?

Quick Search fits situations like: tasks that involve Vector databases; tasks that involve Subagents; tasks that involve Knowledge bases.

How do I install Quick Search in Claude Code?

Run `npx skills add Abilityai/cornelius --skill quick-search -a claude-code`. Or copy the skill folder (.claude/skills/quick-search in Abilityai/cornelius) into .claude/skills/quick-search in your project. Claude Code loads it when a task matches its description.

How do I install Quick Search in Codex?

Run `npx skills add Abilityai/cornelius --skill quick-search -a codex`. Or copy the skill folder (.claude/skills/quick-search in Abilityai/cornelius) into .agents/skills/quick-search in your project. Codex loads it when a task matches its description.

Can I use Quick Search in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Abilityai/cornelius --skill quick-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/quick-search, .gemini/skills/quick-search, .github/skills/quick-search and .opencode/skills/quick-search in your project.

What does Quick Search need to run?

SKILL.md names no scripts, command-line tools or credentials: Quick Search is instructions for the agent only. Its frontmatter pre-approves these tools: Bash, Read.

Does Quick Search access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Quick Search safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Quick Search use?

Quick Search is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Quick Search use?

About 465 tokens (SKILL.md is roughly 1.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Quick Search?

Skills that share tags, products or a category with Quick Search: Logseq Review Workflow (logseq/logseq, 45k stars), Remember (commercetools/ui-kit, 154 stars), Knowledge Ops (affaan-m/ECC, 274k stars) and Skill Development (letta-ai/skills, 147 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Quick Search?

Abilityai (a GitHub organization) maintains it in Abilityai/cornelius, which has 109 GitHub stars. The repository holds 56 skills in this directory. The repository was last updated on September 22, 2026.

Source: Abilityai/cornelius on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.