mcpbeat

Knowledge Priming

techygarg/lattice-knowledge-priming

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.

This is a copy. The original lives at techygarg/knowledge-priming.

632 tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
169
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository 
npx skills add https://github.com/techygarg/lattice --skill knowledge-priming

The instruction itself

5 sections, as written by the author

Knowledge Priming

Config Resolution

  • Look for .lattice/config.yaml in repo root.
  • If found, check paths.knowledge_base for custom doc path.
  • If doc exists at that path, read the full document.
  • STOP: Apply the loaded document as ambient context before any design, implement, or review work begins.
  • If no config, path, or doc found → 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 — guided interview (~10 questions) producing a concise document (~50 lines).

>

> Can also create .lattice/standards/knowledge-base.md manually and reference in .lattice/config.yaml under paths.knowledge_base.

Do not block. Continue without 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?"*

How to use it

Copy the folder

Take techygarg/lattice-knowledge-priming from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.