Capture Conversation
outline/outline
Save the current conversation, a decision, or a set of notes as a document in an Outline collection; use when the user wants to keep what was discussed in their knowledge base.
Load project-specific context -- tech stack, architecture overview, directory layout, trusted sources, and conventions -- so that all skills operate with awareness of what this project actually is.
Install Knowledge Priming
$ npx skills add techygarg/lattice --skill knowledge-priming -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install techygarg/lattice knowledge-priming --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/knowledge-priming .claude/skills/knowledge-priming && rm -rf skills-srcUse ~/.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/
Install the "knowledge-priming" agent skill from https://github.com/techygarg/lattice/tree/main/skills/knowledge-priming into .claude/skills/knowledge-priming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knowledge-priming", 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 install https://github.com/techygarg/lattice/tree/main/skills/knowledge-primingType 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.
$ npx skills add techygarg/lattice --skill knowledge-priming -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install techygarg/lattice knowledge-priming --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/knowledge-priming .agents/skills/knowledge-priming && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "knowledge-priming" agent skill from https://github.com/techygarg/lattice/tree/main/skills/knowledge-priming into .agents/skills/knowledge-priming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knowledge-priming", 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.
$ npx skills add techygarg/lattice --skill knowledge-priming -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install techygarg/lattice knowledge-priming --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/knowledge-priming .cursor/skills/knowledge-priming && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "knowledge-priming" agent skill from https://github.com/techygarg/lattice/tree/main/skills/knowledge-priming into .cursor/skills/knowledge-priming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knowledge-priming", 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 https://github.com/techygarg/lattice.git --path skills/knowledge-priming--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add techygarg/lattice --skill knowledge-priming -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install techygarg/lattice knowledge-priming --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/knowledge-priming .gemini/skills/knowledge-priming && rm -rf skills-srcUse ~/.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/
Install the "knowledge-priming" agent skill from https://github.com/techygarg/lattice/tree/main/skills/knowledge-priming into .gemini/skills/knowledge-priming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knowledge-priming", 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.
$ gh skill install techygarg/lattice knowledge-primingInstalls 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).
$ npx skills add techygarg/lattice --skill knowledge-priming -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/knowledge-priming .github/skills/knowledge-priming && rm -rf skills-srcUse ~/.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/
Install the "knowledge-priming" agent skill from https://github.com/techygarg/lattice/tree/main/skills/knowledge-priming into .github/skills/knowledge-priming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knowledge-priming", 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.
$ npx skills add techygarg/lattice --skill knowledge-priming -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install techygarg/lattice knowledge-priming --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/knowledge-priming .opencode/skills/knowledge-priming && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "knowledge-priming" agent skill from https://github.com/techygarg/lattice/tree/main/skills/knowledge-priming into .opencode/skills/knowledge-priming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "knowledge-priming", 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
knowledge-priming- GitHub stars
- 198
- Token cost
- ~682 tokens
- SKILL.md length
- 269 words
- Files
- 1
- Skills in repo
- 33
- Repo updated
- First seen
- Licence
- MIT
At a glance
Load project-specific context -- tech stack, architecture overview, directory layout, trusted sources, and conventions -- so that all skills operate with awareness of what this project actually is.
- Works in 6 steps: Look for .lattice/config.yaml in the… → If found, check paths.knowledge_base for… → If a document exists at that path, read… → …
- A knowledge base document exists
- SKILL.md covers Config Resolution, When No Document Exists, What the Document Contains and Scope Boundary
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Knowledge Priming is an agent skill from techygarg/lattice. Load project-specific context -- tech stack, architecture overview, directory layout, trusted sources, and conventions -- so that all skills operate with awareness of what this project actually is. Use when a knowledge base document exists, or when the user asks about the project's tech stack, architecture, conventions, framework, directory layout, or says 'tell me about this project', 'what are we using?', 'what's our stack?', or 'what framework is this?'. Use the knowledge-priming-refiner to create a knowledge…
Its SKILL.md is about 680 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 Knowledge bases. The repository describes itself as: Install engineering discipline into any AI coding assistant. Composable skills for design, implementation, review, and team standards. Better process, not just better prompts. The licence is MIT.
When your agent uses it
- A knowledge base document exists
- The user asks about the projects tech stack
- Directory layout
- Says tell me about this project
Example prompts
- “tell me about this project”
- “what are we using?”
- “s our stack?”
- “/knowledge-priming”
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Look for .lattice/config.yaml in the repo root.
- If found, check paths.knowledge_base for a custom document path.
- If a document exists at that path, read the full document.
- STOP: Apply the loaded document as ambient context before any design, implementation, or review work begins.
- If a path is configured but no document exists at it → tell the user which configured path is missing, then see "When No Document Exists".
- If there is no config file or no paths.knowledge_base key → see "When No Document Exists".
What it can do on your machine
Read from SKILL.md and the folder at commit 4d6c35f. 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
No scripts in the folder and no shell commands in SKILL.md.
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
Knowledge Priming loads about 682 tokens when it runs. Until then it costs about 138 tokens; SKILL.md has 269 words of instructions outside code blocks.
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 techygarg/lattice at commit 4d6c35f, republished under its MIT licence (© techygarg). 269 words, ~682 tokens.
Download SKILL.mdSave it as
.claude/skills/knowledge-priming/SKILL.md (or your agent's skills folder).- name
- knowledge-priming
- description
- Load project-specific context -- tech stack, architecture overview, directory layout, trusted sources, and conventions -- so that all skills operate with awareness of what this project actually is. Use when a knowledge base document exists, or when the user asks about the project's tech stack, architecture, conventions, framework, directory layout, or says 'tell me about this project', 'what are we using?', 'what's our stack?', or 'what framework is this?'. Use the knowledge-priming-refiner to create a knowledge base document.
Knowledge Priming
Config Resolution
- Look for
.lattice/config.yamlin the repo root. - If found, check
paths.knowledge_basefor a custom document path. - If a document exists at that path, read the full document.
- STOP: Apply the loaded document as ambient context before any design, implementation, or review work begins.
- If a path is configured but no document exists at it → tell the user which configured path is missing, then see "When No Document Exists".
- If there is no config file or no
paths.knowledge_basekey → see "When No Document Exists".
When No Document Exists
Inform the user:
No project knowledge base found. AI skills will operate from generic assumptions about tech stack, architecture, and conventions.
To create one, trigger knowledge-priming-refiner — a guided interview (~10 questions) producing a concise document (~50 lines).
You can also create
.lattice/standards/knowledge-base.mdmanually and reference it in.lattice/config.yamlunderpaths.knowledge_base.
Do not block. Continue without the knowledge base.
What the Document Contains
| # | Section | What It Captures |
|---|---|---|
| 1 | Architecture Overview | App type, major components, how they interact |
| 2 | Tech Stack and Versions | Specific technologies with version numbers, including "not X" clarifications |
| 3 | Curated Knowledge Sources | Official docs, trusted blogs, internal references (5–10 max) |
| 4 | Project Structure | Directory layout showing where things live |
| 5 | Project Conventions | Project-specific conventions other skills cannot infer from code |
Scope Boundary
| Concern | Owned By |
|---|---|
| Coding style, naming principles, function design | clean-code atom |
| Architectural layers, dependency direction | architecture atom |
| Domain modeling, aggregate design | domain-driven-design atom |
| Input validation, injection prevention | secure-coding atom |
| Test structure, assertion quality | test-quality atom |
Knowledge priming answers "what are we working with?" — not "how should we write?"
© techygarg, 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 skills/knowledge-priming of techygarg/lattice.
Open the folder on GitHubat commit 4d6c35f
Compare with similar skills
Knowledge Priming 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Knowledge Priming this skilltechygarg/lattice | 198 | — | ~682 | Automated safety check: Pass | MIT | |
| Capture Conversationoutline/outline | 41k | — | ~474 | Automated safety check: Pass | Custom licence | |
| Project CairniBlinkQ/project-cairn | 235 | 2 repos | ~861 | Automated safety check: Pass | MIT | |
| LLM Wiki Knowledge GraphEgonex-AI/Understand-Anything | 86k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Find And Citeoutline/outline | 41k | — | ~537 | Automated safety check: Pass | Custom licence | |
| Xhs Virtual Productchenjin-cmd/xhs-virtual-product | 727 | — | ~862 | Automated safety check: Pass | MIT |
Similar skills
Project Cairn
iBlinkQ/project-cairn
Standardize how an AI-collaboration project turns work into reusable knowledge.
LLM Wiki Knowledge Graph
Egonex-AI/Understand-Anything
Detects a Karpathy-pattern LLM wiki and builds an interactive knowledge graph with entities, implicit relationships and topic clusters.
Find And Cite
outline/outline
Answer questions from the Outline knowledge base with quotes and links to the source documents; use when the user asks what the team knows, documented, or decided about a topic.
Xhs Virtual Product
chenjin-cmd/xhs-virtual-product
This skill helps plan, select, produce, and market Xiaohongshu (RED) virtual/digital products — templates, knowledge bases, test tools, study materials.
Openkb
VectifyAI/OpenKB
A skill your agent uses when the user asks about content in their OpenKB knowledge base — research topics, concepts compiled from their documents, cross-document synthesis — or mentions openkb, an…
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Related
Categories
Questions about Knowledge Priming
What does Knowledge Priming do?
Load project-specific context -- tech stack, architecture overview, directory layout, trusted sources, and conventions -- so that all skills operate with awareness of what this project actually is. Knowledge Priming is an agent skill from techygarg/lattice. Load project-specific context -- tech stack, architecture overview, directory layout, trusted sources, and conventions -- so that all skills operate with awareness of what this project actually is.
When should I use Knowledge Priming?
Knowledge Priming fits situations like: A knowledge base document exists; the user asks about the projects tech stack; directory layout; says tell me about this project.
How do I install Knowledge Priming in Claude Code?
Run `npx skills add techygarg/lattice --skill knowledge-priming -a claude-code`. Or copy the skill folder (skills/knowledge-priming in techygarg/lattice) into .claude/skills/knowledge-priming in your project. Claude Code loads it when a task matches its description.
How do I install Knowledge Priming in Codex?
Run `npx skills add techygarg/lattice --skill knowledge-priming -a codex`. Or copy the skill folder (skills/knowledge-priming in techygarg/lattice) into .agents/skills/knowledge-priming in your project. Codex loads it when a task matches its description.
Can I use Knowledge Priming 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 techygarg/lattice --skill knowledge-priming -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/knowledge-priming, .gemini/skills/knowledge-priming, .github/skills/knowledge-priming and .opencode/skills/knowledge-priming in your project.
What does Knowledge Priming need to run?
SKILL.md names no scripts, command-line tools or credentials: Knowledge Priming is instructions for the agent only.
Does Knowledge Priming 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 Knowledge Priming 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 Knowledge Priming use?
Knowledge Priming 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 Knowledge Priming use?
About 682 tokens (SKILL.md is roughly 2.7k 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 Knowledge Priming?
Skills that share tags, products or a category with Knowledge Priming: Capture Conversation (outline/outline, 41k stars), Project Cairn (iBlinkQ/project-cairn, 235 stars), LLM Wiki Knowledge Graph (Egonex-AI/Understand-Anything, 86k stars) and Find And Cite (outline/outline, 41k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Knowledge Priming?
techygarg (a GitHub user) maintains it in techygarg/lattice, which has 198 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 6, 2026.
Source: techygarg/lattice on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.