Session Handoff Prompt

COMPASS Skills

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> Start here: Use & develop your own Skill ecosystem > > A practical tutorial for using SKILL.md, auditing reusable skills, drafting skills with AI, extracting real workflows, and building a local Skill ecosystem.

npx skills add dongshuyan/compass-skills --skill '*' -a claude-code

COMPASS Skills gives AI agents nine local skills: five runtime collaboration skills, two run-history skill-engineering skills, one academic humanization skill, and one local hiring-support skill.

The project currently ships nine SKILL.md skills:

For multi-skill repositories, install only the functions you actually need. Use pause-and-resume when the same AI conversation will remain available; use session-handoff-prompt when work must move to a fresh conversation. The run-history pair supports skill engineering, and academic-humanizer improves academic prose without changing its claims.

Quick Start

List the available skills before installing:

npx skills add dongshuyan/compass-skills --list

Install all skills for Claude Code:

npx skills add dongshuyan/compass-skills --skill '*' -a claude-code

Install all skills for both Codex and Claude Code:

npx skills add dongshuyan/compass-skills --skill '*' -a codex -a claude-code

After installation, invoke the skills directly in an AI conversation:

$task-clarifier
$task-forest
$pause-and-resume
$session-handoff-prompt
$user-profile-keeper
$run-history-skill-builder
$run-history-skill-upgrader
$academic-humanizer
$assess-interview-candidate

For manual installation, copy the nine folders under skills/ into the agent's local skills directory and keep their references/, scripts/, assets/, evals/, and agents/ subdirectories intact.

Why COMPASS Exists

Long-running agent work needs five kinds of state:

• User context: communication preferences, risk boundaries, recurring omissions, and collaboration style.
• Project context: where the current request fits, what it depends on, and how far it has progressed.
• Goal context: how the current task contributes to the original objective and whether it still matches it.
• Pause context: the safe stopping point, remaining work, non-repeatable effects, and first action when the same AI conversation resumes.
• Handoff context: what a new AI conversation needs to continue the current task without replaying the whole transcript.

COMPASS organizes that state into five local workflows:

1. A local profile that the user can inspect and correct.
2. A repo-local task graph that survives AI conversation boundaries.
3. A cooperative pause checkpoint for continuing in the same AI conversation.
4. A paste-ready continuation prompt for a new AI conversation.
5. A clarification gate before ambiguous or risky execution.

How The Core And Meta Skills Work Together

task-clarifier is the entry point for ambiguous, high-cost, high-risk, evidence-sensitive, or externally visible work. It first identifies the user-owned decisions that must be made, asks 1-3 focused questions with recommended answers, confirms shared understanding, and only then searches or executes.

task-forest records long-running work structure: why a task exists, where it fits, how far it progressed, what changed, and what remains unresolved.

pause-and-resume stops an unfinished task at the nearest safe boundary, records what must and must not be repeated, and continues from that checkpoint when the user returns to the same AI conversation. It creates no file solely for pausing.

session-handoff-prompt turns the current AI conversation, explicit transcripts, workspace evidence, and optional task-forest exports into a concise prompt for the next AI conversation. It reads task-forest as structured context but never modifies it.

user-profile-keeper stores collaboration preferences locally. Future AI conversations use the profile to ask relevant questions and apply the right risk boundary. Current files, logs, and user-provided context remain the authority; secrets stay out of the profile.