Agent skill

Doc Search

Search project documentation — ADRs, wiki entries, conventions via ripgrep, qmd, fff, and ctx

MITAuto-check passedKnowledge Management

Install Doc Search

skills CLI

$ npx skills add jellydn/my-ai-tools --skill doc-search -a claude-code

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

GitHub CLI

$ gh skill install jellydn/my-ai-tools doc-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/jellydn/my-ai-tools.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/doc-search .claude/skills/doc-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/

Paste into Claude Code

Install the "doc-search" agent skill from https://github.com/jellydn/my-ai-tools/tree/main/skills/doc-search into .claude/skills/doc-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doc-search", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/jellydn/my-ai-tools/tree/main/skills/doc-search

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add jellydn/my-ai-tools --skill doc-search -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install jellydn/my-ai-tools doc-search --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/jellydn/my-ai-tools.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/doc-search .agents/skills/doc-search && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "doc-search" agent skill from https://github.com/jellydn/my-ai-tools/tree/main/skills/doc-search into .agents/skills/doc-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doc-search", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add jellydn/my-ai-tools --skill doc-search -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install jellydn/my-ai-tools doc-search --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/jellydn/my-ai-tools.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/doc-search .cursor/skills/doc-search && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "doc-search" agent skill from https://github.com/jellydn/my-ai-tools/tree/main/skills/doc-search into .cursor/skills/doc-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doc-search", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/jellydn/my-ai-tools.git --path skills/doc-search

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add jellydn/my-ai-tools --skill doc-search -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install jellydn/my-ai-tools doc-search --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/jellydn/my-ai-tools.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/doc-search .gemini/skills/doc-search && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "doc-search" agent skill from https://github.com/jellydn/my-ai-tools/tree/main/skills/doc-search into .gemini/skills/doc-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doc-search", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install jellydn/my-ai-tools doc-search

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add jellydn/my-ai-tools --skill doc-search -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/jellydn/my-ai-tools.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/doc-search .github/skills/doc-search && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "doc-search" agent skill from https://github.com/jellydn/my-ai-tools/tree/main/skills/doc-search into .github/skills/doc-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doc-search", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add jellydn/my-ai-tools --skill doc-search -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install jellydn/my-ai-tools doc-search --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/jellydn/my-ai-tools.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/doc-search .opencode/skills/doc-search && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "doc-search" agent skill from https://github.com/jellydn/my-ai-tools/tree/main/skills/doc-search into .opencode/skills/doc-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doc-search", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: doc-search
GitHub stars: 123
Token cost: ~1.4k tokens
SKILL.md length: 421 words
Files: 1
Skills in repo: 33
Repo updated: Oct 10, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Search project documentation — ADRs, wiki entries, conventions via ripgrep, qmd, fff, and ctx

Works in 4 steps: Find Relevant Documents → Query Knowledge Base → Search Past Sessions → …
Tasks that involve Architecture decision records
SKILL.md covers When to Use, What It Does, Where Documentation Lives and How to Search, plus 4 more sections
Calls rg

What it does

Doc Search is an agent skill from jellydn/my-ai-tools. Search project documentation — ADRs, wiki entries, conventions via ripgrep, qmd, fff, and ctx

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: cline, claude, opencode, amp, codex, gemini, cursor, pi

It sits in Knowledge Management, covering Architecture decision records. The repository describes itself as: Comprehensive configuration management for AI coding tools - Replicate my complete setup for Claude Code, OpenCode, Amp, Li, Codex and Claude Code Switch with custom… The licence is MIT.

When your agent uses it

Tasks that involve Architecture decision records

Example prompts

“/doc-search”

Requirements

Compatibility (from SKILL.md): cline, claude, opencode, amp, codex, gemini, cursor, pi

Workflow steps

4 steps, taken from the step headings in SKILL.md.

Find Relevant Documents
Query Knowledge Base
Search Past Sessions
Explore by Pattern

What it can do on your machine

Read from SKILL.md and the folder at commit 62c9227. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- rg
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.
Compatibility
cline, claude, opencode, amp, codex, gemini, cursor, pi
From compatibility in the SKILL.md frontmatter.

Context cost

Doc Search loads about 1.4k tokens when it runs. Until then it costs about 26 tokens; SKILL.md has 421 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~26
When it runs · the whole SKILL.md, loaded when a task matches: ~1.4k

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 passed

The automated check found no risky patterns in SKILL.md.

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 jellydn/my-ai-tools at commit 62c9227, republished under its MIT licence (© jellydn). 421 words, ~1,370 tokens.

Download SKILL.mdSave it as .claude/skills/doc-search/SKILL.md (or your agent's skills folder).

name: doc-search
description: Search project documentation — ADRs, wiki entries, conventions via ripgrep, qmd, fff, and ctx
compatibility: cline, claude, opencode, amp, codex, gemini, cursor, pi
license: MIT
hint: Use when you need to find existing documentation before writing new docs
user-invocable: true

Documentation Search

When to Use

Use this skill when:

Starting work on a feature that may have existing decisions or ADRs
Need to understand project conventions or patterns
Looking for past design discussions or trade-off analyses
Want to find relevant wiki entries or knowledge base articles
Need to understand how existing documentation is structured
Planning to write documentation and want to match existing style

What It Does

Helps you find and navigate existing project documentation using available tools (grep, qmd, fff, ctx). Documentation is often scattered across multiple locations — this skill provides a systematic approach to find what you need.

Where Documentation Lives

This project stores documentation in several locations:

Location	Content	Best For
`docs/`	User-facing guides (quick-start, tutorials)	Getting started, feature guides
`ADRs` via `configs/adr/*`	Architecture Decision Records	Why decisions were made
`wiki/`	LLM wiki — entities, concepts, log	Knowledge base, cross-references
`MEMORY.md`	Durable project learnings and gotchas	Known issues, conventions
`skills/*/SKILL.md`	Agent skill definitions	Tool capabilities
`configs/*.md`	Tool-specific documentation	Per-tool behavior
`AGENTS.md`	Agent instructions and guidelines	Development workflow
qmd knowledge base	Indexed project knowledge	Searchable, AI-powered retrieval

How to Search

Step 1: Find Relevant Documents

Use fff to locate documentation files:

bash

fff "*.md" docs/         # All documentation files
fff "*adr*"              # Architecture Decision Records
fff "*auth*" docs/       # Auth-related documentation
fff "*wiki*"             # Wiki entries

Use rg (ripgrep) to search documentation content:

bash

rg "decision" docs/                   # Find decisions in docs
rg "ADR-0" . --glob "*.md"           # Find ADR references
rg "rate.limiting" --glob "*.md"     # Find docs about rate limiting

Step 2: Query Knowledge Base

Use qmd to search durable project knowledge:

bash

qmd search "authentication decisions"     # Find related knowledge
qmd query "What architecture exists for X?"  # Get structured answers
qmd get ADR-001                           # Get a specific ADR

The qmd knowledge base indexes project learnings, ADRs, conventions, and gotchas that persist across agent sessions.

Step 3: Search Past Sessions

Use ctx to find previous discussions about documentation:

bash

ctx search "documentation" "decision"       # Past doc discussions
ctx search "ADR" "architecture" path/docs/  # Past ADR discussions
ctx search "convention" "pattern"            # Past convention discussions

Step 4: Explore by Pattern

Project documentation follows consistent patterns:

Architecture Decision Records (ADRs):

bash

# Find all ADRs
ls -la docs/adr/
# Search ADR content
rg "decision" docs/adr/

Wiki entries:

bash

# Browse wiki structure
ls -la wiki/wiki/entities/
ls -la wiki/wiki/concepts/
# Search wiki content
rg "topic" wiki/wiki/ --glob "*.md"

Agent skills:

bash

# Find skill documentation
rg "what.*does" skills/*/SKILL.md
# Find skills by category
rg "compatibility:.*auth" skills/*/SKILL.md

Show full SKILL.md (163 more words)Show less

Understanding Documentation Style

Before writing new documentation, study existing examples:

Pick a reference: Find an existing doc on a similar topic
Analyze structure: Note heading levels, code blocks, tables
Check tone: Is it formal, conversational, or technical?
Match conventions: Use the same formatting patterns

Example: If you need to write an ADR, read an existing ADR first:

bash

fff "*adr*.md"   # Find existing ADRs
cat docs/adr/001-some-decision.md  # Read as reference

Documentation Discovery Workflow

Before writing:
1. Search existing docs for related content
2. Check qmd for existing knowledge
3. Search ctx for past discussions
4. Read existing docs for style reference

During writing:
5. Link to relevant ADRs and decisions
6. Reference existing conventions
7. Cross-link related documentation

After writing:
8. Add to wiki or qmd knowledge base
9. Reference from relevant agent instructions
10. Update docs-update skill if patterns changed

Integration with Other Skills

docs-update: Use doc-search first to find what exists before updating
context-discovery: Documentation search is part of context discovery
implementation-logger: Extract learnings into documentation
qmd-knowledge: Add new knowledge to durable storage
llm-wiki: Build and maintain wiki entries from findings

Tips

Search before writing: Always check if documentation already exists
Follow existing patterns: Match the style of existing docs
Cross-link: Reference ADRs, wiki entries, and related docs
Update qmd: After finding useful documentation, index it in qmd
Use rg over grep: ripgrep is faster and respects .gitignore
Check wiki/ first: The LLM wiki is designed for discoverability

Files

Just SKILL.md in skills/doc-search of jellydn/my-ai-tools.

Open the folder on GitHubat commit 62c9227

Compare with similar skills

Doc 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.

Doc Search compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Doc Search this skilljellydn/my-ai-tools	123	—	~1.4k	Automated safety check: Pass	MIT	today
Grasp Knowledgedykyi-roman/awesome-claude-code	104	—	~1.4k	Automated safety check: Pass	MIT	1 mo ago
Exploremirumee/nimara-ecommerce	129	—	~436	Automated safety check: Pass	BSD-3-Clause	today
Research Lintiusztinpaul/ai-research-os-workshop	179	—	~2.3k	Automated safety check: Pass	MIT	3 mo ago
New LoopAI-Builder-Club/skills	1.3k	—	~1.2k	Automated safety check: Notes	None	24 days ago
Pi Reviewnatsukium/dotfiles	106	—	~972	Automated safety check: Pass	CC0-1.0	today

Similar skills

Grasp Knowledge
dykyi-roman/awesome-claude-code
GRASP principles knowledge base for PHP 8.4 projects. An agent skill from dykyi-roman/awesome-claude-code.
104 GitHub stars~1.4k tokensUpdated 1 mo ago
Knowledge ManagementAuto-check passed
Explore
mirumee/nimara-ecommerce
Ways to explore llm-wiki and answer from it. An agent skill from mirumee/nimara-ecommerce.
129 GitHub stars~436 tokensUpdated today
Knowledge ManagementAuto-check passed
Research Lint
iusztinpaul/ai-research-os-workshop
Health-check a research directory produced by /research. An agent skill from iusztinpaul/ai-research-os-workshop.
179 GitHub stars~2.3k tokensUpdated 3 mo ago
Knowledge ManagementAuto-check passed
New Loop
AI-Builder-Club/skills
Spin up a new loop (domain) in a file-based knowledge base — bootstrap the substrate if it's missing, gather the loop's charter, scaffold domains/<loop/README.md, then do ONE real test run and…
1.3k GitHub stars~1.2k tokensUpdated 24 days ago
Knowledge ManagementAuto-check: notes
Pi Review
natsukium/dotfiles
Delegate a source-grounded design or code review to a fresh pi CLI process using sol or luna, then address verified findings until no blockers remain.
106 GitHub stars~972 tokensUpdated today
Knowledge ManagementAuto-check passed
Kdrive Sentry Rca
Infomaniak/desktop-kDrive
Investigate kDrive crashes, Sentry issues, and application logs to produce source-grounded root cause analyses.
120 GitHub stars~4.1k tokensUpdated today
Knowledge ManagementAuto-check passed

Questions about Doc Search

What does Doc Search do?

Search project documentation — ADRs, wiki entries, conventions via ripgrep, qmd, fff, and ctx. Doc Search is an agent skill from jellydn/my-ai-tools.

When should I use Doc Search?

Doc Search fits situations like: tasks that involve Architecture decision records.

How do I install Doc Search in Claude Code?

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

How do I install Doc Search in Codex?

Run `npx skills add jellydn/my-ai-tools --skill doc-search -a codex`. Or copy the skill folder (skills/doc-search in jellydn/my-ai-tools) into .agents/skills/doc-search in your project. Codex loads it when a task matches its description.

Can I use Doc 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 jellydn/my-ai-tools --skill doc-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/doc-search, .gemini/skills/doc-search, .github/skills/doc-search and .opencode/skills/doc-search in your project.

What does Doc Search need to run?

Going by SKILL.md and its folder, Doc Search needs the command-line tools its instructions call (rg). Compatibility (from SKILL.md): cline, claude, opencode, amp, codex, gemini, cursor, pi.

Does Doc 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 Doc Search safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Doc Search use?

Doc Search is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Doc Search use?

About 1.4k tokens (SKILL.md is roughly 5.5k 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 Doc Search?

Skills that share tags, products or a category with Doc Search: Grasp Knowledge (dykyi-roman/awesome-claude-code, 104 stars), Explore (mirumee/nimara-ecommerce, 129 stars), Research Lint (iusztinpaul/ai-research-os-workshop, 179 stars) and New Loop (AI-Builder-Club/skills, 1.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Doc Search?

jellydn (a GitHub user) maintains it in jellydn/my-ai-tools, which has 123 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 10, 2026.

Source: jellydn/my-ai-tools on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Doc Search

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Compatibility

Context cost

Safety

SKILL.md

Documentation Search

When to Use

What It Does

Where Documentation Lives

How to Search

Step 1: Find Relevant Documents

Step 2: Query Knowledge Base

Step 3: Search Past Sessions

Step 4: Explore by Pattern

Understanding Documentation Style

Documentation Discovery Workflow

Integration with Other Skills

Tips

Files

Compare with similar skills

Similar skills

More from jellydn/my-ai-tools

Related

Questions about Doc Search