Shapes agent behavior via instruction framing and style transfer. Use when composing dispatch prompts or writing skill instructions for parallel review agents.
npx skills add https://github.com/athola/claude-night-market --skill latent-space-engineering
Shape agent behavior by framing instructions for
optimal performance. Distinct from context engineering
(packing the right information), this skill addresses
HOW instructions are framed to put agents in productive
mental states.
an existing style
Replace threat-based prompting with calm, confident
instructions. Fear-based prompts cause rushing and
corner-cutting.
Load module: modules/emotional-framing.md
Inject exemplar code or prose into context before
requesting output. Agents reproduce stylistic
attributes from pre-loaded samples.
Load module: modules/style-gene-transfer.md
Frame multi-agent review dispatch with competitive
incentives to increase rigor and thoroughness.
Load module: modules/competitive-review.md
| Technique | When | Module |
|-----------|------|--------|
| Emotional framing | Any agent prompt | emotional-framing |
| Style gene transfer | Code/doc generation | style-gene-transfer |
| Competitive review | 3+ parallel reviewers | competitive-review |
"don't fail", "or else"); replaced with calm, confident framing
per modules/emotional-framing.md
least one exemplar sample is injected into context before the
output is requested (style gene transfer applied)
prompt includes a competitive framing element per
modules/competitive-review.md
irrelevant modules are not loaded (token efficiency maintained)
Use when creating new skills, editing existing skills, or verifying skills work before deployment
Curated collection of high-quality prompts for various use cases. Includes role-based prompts, task-specific templates, and prompt refinement techniques. Use when user needs prompt templates, role-play prompts, or ready-to-use prompt examples for coding, writing, analysis, or creative tasks.
Convert abstract edge concepts into strategy draft variants and optional exportable ticket YAMLs for edge-candidate-agent export/validation.
INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.
Analyze the protocol layer between agent harness and LLM model. Use when (1) understanding message wire formats and API contracts, (2) examining tool call encoding/decoding mechanisms, (3) evaluating streaming protocols and partial response handling, (4) identifying agentic chat primitives (system prompts, scratchpads, interrupts), (5) comparing multi-provider abstraction strategies, or (6) understanding how frameworks translate between native LLM APIs and internal representations.
Translate SKILL.md and README.md files into multiple languages for sharing skills internationally
| Shared workflow for editing Langfuse's repo-owned agent setup under `.agents/`. Use when changing AGENTS files, shared skills, `.agents/config.json`, generated shim behavior, provider discovery paths, or install-time agent sync.
>- Summarizes Google Cloud Data Lineage graphs to help users debug data quality issues and understand data provenance for BQ/GCS. Use when summarizing upstream and downstream data flows, and presenting complex lineage data as an intuitive Markdown report. Don't use for generic BigQuery queries, editing lineage relationships, or downstream deprecation. Don't use for downstream blast-radius impact analysis (use datalineage-bigquery-asset-impact-analysis skill instead).
Take athola/latent-space-engineering from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
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.