Agent skill · AI & Agents

composing-context

Internal pattern guide for composing turn-local retrieval-gated context into a synthetic user-message preface. Documents the `composePreface` helper in `@atlas/core/agent-context/compose-preface`. Loaded by infrastructure code that assembles per-turn LLM input — not user-invocable.

Friday Platform98★ · 1 repos on radarProfile →
claude-codeNOASSERTION
Install
npx skills add friday-platform/friday-studio --skill composing-context --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 6 KB
Bundled scripts: none
Path: packages/system/skills/composing-context/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 98
Language: TypeScript
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Composing turn-local context as a synthetic user-message preface This skill documents the **synthetic user-message preface** pattern used by Friday's chat supervisor and FSM `type: llm` actions to surface turn-local retrieved content (artifacts, narrative memory, temporal facts, future on-demand retrieval) to the model. ## Why a synthetic preface and not the system prompt Per-turn data does not

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About this skill
What does the composing-context skill do?

Internal pattern guide for composing turn-local retrieval-gated context into a synthetic user-message preface. Documents the `composePreface` helper in `@atlas/core/agent-context/compose-preface`. Loaded by infrastructure code that assembles per-turn LLM input — not user-invocable.

How do I install it?

Run `npx skills add friday-platform/friday-studio --skill composing-context --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From friday-platform/friday-studio, a repository with 98 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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