knowledge-priming
Skill209 starsChanged 2 months agoMITView on GitHub
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.
We split this skill into the rules it gives an agent
6 rules. About 0 are common, 3 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 10
Look for .lattice/config.yaml in the repo root.
- Very specific: line 11
If found, check paths.knowledge_base for a custom document path.
- Distinctive: line 12
If a document exists at that path, read the full document.
- Distinctive: line 14
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".
- Very specific: line 15
If there is no config file or no paths.knowledge_base key → see "When No Document Exists".
- Distinctive: line 27
Do not block. Continue without the knowledge base.
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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?"
In this repository28 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- architecture-compassSkill
- architecture-refinerSkill
- architectureSkill
- bug-fixSkill
- clean-code-refinerSkill
- clean-codeSkill
- code-forgeSkill
- collaborative-judgmentSkill
- context-anchoringSkill
- ddd-refinerSkill
- design-blueprintSkill
- design-firstSkill
- domain-driven-designSkill
- knowledge-priming-refinerSkill
- language-idioms-refinerSkill
- lattice-initSkill
- learning-harvestSkill
- refactor-safelySkill
- refiners-updateSkill
- requirement-forge-refinerSkill
- requirement-forgeSkill
- requirement-qualitySkill
- review-refinerSkill
- reviewSkill
- secure-codingSkill
- test-qualitySkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.