Search Queries

Community

jstanden

search-queries

Cerb's search query language -- the filter:expression grammar, one syntax per filter type, deep search, boolean groups, and sorting. Load it before writing a worklist query, a saved search, or a `record_query:`.

Overview

Publisher	jstanden
Repository	`cerb`
Skill name	`search-queries`
Stars	83
Forks	38
Bundled files	Instructions only
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by jstanden on GitHub. Read the source before you install it.

Installation

Install the Search Queries AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/jstanden/cerb/tree/12.0.x/features/cerberusweb.core/assets/agent_filesystems/cerb-agents/skills/search-queries
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/jstanden/cerb/tree/12.0.x/features/cerberusweb.core/assets/agent_filesystems/cerb-agents/skills/search-queries

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/jstanden/cerb.git /tmp/cerb
mkdir -p .claude/skills
cp -r /tmp/cerb/features/cerberusweb.core/assets/agent_filesystems/cerb-agents/skills/search-queries .claude/skills/search-queries

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Search Queries in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Search Queries on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Search Queries is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Cerb search queries

The text language Cerb uses to filter records in worklists, saved searches, API requests, and automations (record_query: in record.search: / data.query:).

Writing one is two jobs: knowing the GRAMMAR (this skill) and knowing which filter keys a record type actually exposes (the records skill — cerb records filters <type> is the authority, and it reports THIS install including its custom fieldsets).

Method

Identify the target record type. Never assume it; if it's genuinely ambiguous, ask, otherwise state what you assumed.
Look up the filters that record type actually exposes before writing them — cerb records filters <type> is the fastest authority. Never invent a filter name; an unknown filter fails the whole query.
Match the expression syntax to the filter's TYPE (text, fulltext, number, boolean, date, chooser, record/deep-search, links, watchers, nullness).
Give the query, then explain each non-obvious filter in one line.
Offer a tighter or looser variant when the result set is likely too broad or too narrow (a date bound, a sort:, a deep search instead of a guess).

Syntax cheat sheet (verify specifics against the docs)

A query is space-separated filter:expression pairs, AND-ed by default.
text: status:open subject:"a phrase" mask:abc* color:[red,green] status:!open
fulltext: bare terms, content:("exact phrase" other terms), text:!(not these words)
numbers: age:35 priority:!1 age:>21 order:<=100 importance:25...75 importance:[0,50,75]
booleans: checkbox:y / isAdmin:n (yes/y/true, no/n/false)
dates: a bare value is a SINCE bound -- created:"-1 month" means that point up to now. Join two with to to bound both ends: created:"January 1 to June 30", created:"-1 year to -6 months", created:"big bang to first day of this month".
date shortcuts -- one word for a whole period, so reach for these before writing a range. created:"this year", and likewise last year / next year, this month / last month / next month, this week / last week / next week, plus today, yesterday, tomorrow. Each expands to a bounded range rather than a since-bound (this year is Jan 1 to Dec 31; today is 00:00:00 to 23:59:59), which is the difference that catches people out.
dates, advanced: created:(since:"-1 week" until:now months:Jan,Feb,Mar days:Weekdays times:9a-5p)
nullness: sla.level:null / checkbox:!null
choosers (*.id:): group.id:1 group.id:[1,2,3] — numeric expressions
links: links:ticket links.ticket:(mask:a*)
watchers: watchers:me watchers:any watchers:none watchers:kina,karl watchers:1,2,3
deep search: the expression is a full query on the linked type — group:(name:S*), chainable messages.first:(sender:(org:(region:Europe))), negatable group:!(name:S*)
boolean groups: OR between filters, parentheses to group, !(...) to negate
sorting: sort:subject sort:-updated sort:-importance,created
search indexes expose their own filter: keyword supporting * (prefix), ~ (stemming), and top:N ranking — e.g. title:(11.1* release~ top:10)

Ground truth

/cerb-docs/references/docs/search.md — the complete query language, and the authority for SYNTAX. cerb records gives you keys and types, not grammar.

For runtime discovery inside an automation, /cerb-docs/references/docs/data-queries/record/filters.md documents the type:record.filters of:<type> data query.

Before telling anyone a filter doesn't exist, confirm with cerb records filters — then offer the nearest alternative, usually a deep search through a link.

Output

Present a query for the UI or a saved search as a single line. For an automation, show it in KATA context under record_query:. When someone's input is interpolated into a query, use record_query_params: with ${name} placeholders rather than pasting raw values into the query text.

Frequently asked questions

What does the Search Queries AI skill do?

Why use Search Queries on TypingMind?

Because you install it once and use it with any model. Search Queries is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Search Queries in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jstanden/cerb/tree/12.0.x/features/cerberusweb.core/assets/agent_filesystems/cerb-agents/skills/search-queries. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Search Queries?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Search Queries?

As many as you like. As long as a model supports skills, you can use Search Queries with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Search Queries AI skill free?

It is published on GitHub by jstanden. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Cerb search queries

Method

Syntax cheat sheet (verify specifics against the docs)

Ground truth

Output

Frequently asked questions

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