mixed-initiative-flow

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Repo stars 108
License MIT
Author repo ai-design-skills

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: When the AI leads vs. when the user leads, and how to hand off control. Mixed-initiative interaction is when both the human and…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “Initiative Spectrum”, “Designing Initiative Handoffs”, “When the AI Should Lead”, “When the User Should Lead”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name mixed-initiative-flow directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “Initiative Spectrum / Designing Initiative Handoffs / When the AI Should Lead” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / shell-exec; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

Mixed-Initiative Flow

Mixed-initiative interaction is when both the human and the AI can take the lead. The designer decides who drives at each moment — and how control transfers between them.

Initiative Spectrum

Interactions sit on a spectrum:

User-driven: The user gives instructions, the AI executes. The user controls pace, direction, and scope.
AI-driven: The AI leads — asking questions, making suggestions, guiding the user through a process.
Shared: Both parties contribute. The AI proposes, the user edits. The user starts, the AI finishes. Most AI products default to user-driven. The interesting design space is in shared and AI-driven modes.

Designing Initiative Handoffs

The moment control shifts from one party to the other is where most interactions fail. Design these transitions:

Explicit handoff: "I've drafted three options. Which direction do you want to go?" — the AI clearly passes control.
Implicit handoff: The AI stops generating and waits, signalling the user's turn through UI affordance.
Negotiated handoff: "I could take this further or stop here for your input. What do you prefer?"
Forced handoff: The AI encounters a decision it can't make and must hand back to the human.

When the AI Should Lead

The AI should take initiative when:

The user is uncertain or exploring and needs guidance
The task has a known best-practice sequence the AI can walk through
The user has explicitly asked for help or coaching
Proactive suggestions would save time without being intrusive

When the User Should Lead

The user should retain control when:

The task involves subjective judgment or creative direction
Stakes are high and errors are costly
The user has strong domain expertise
Privacy or consent decisions are involved

Anti-Patterns

Initiative whiplash: Control bouncing back and forth too rapidly
Passive AI: Never taking initiative even when it would help
Overbearing AI: Taking over when the user wants control
Unclear ownership: Neither party knows whose turn it is

Design Artefacts

Initiative maps showing who leads at each stage
Handoff trigger definitions (what causes a transfer of control)
Autonomy level specifications per feature area

Fluxly profile Author and license come from source; runtime, permissions, and network are Fluxly detections or estimates

Fluxly category: Other
Author-declared agents: No explicit declaration found; this is not inferred or tested compatibility
Static check: 94 / 100 · heuristic scan, not runtime safety proof
Author / version / license: @Owl-Listener · MIT
Fluxly token estimate: Lean
Fluxly setup estimate: Guided setup
External API key: No requirement detected
Detected OS requirements: Unspecified
Runtime requirements: Unspecified
Detected file/system behavior: Read-only
Shell exec
Detected network behavior: Local-only
Install commands: None (reference only)

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview mixed-initiative-flow.preview

The current SKILL.md does not define a fixed output example.

SKILL.md SKILL.md

# Mixed-Initiative Flow
Mixed-initiative interaction is when both the human and the AI can take the lead. The designer decides who drives at each moment — and how control transfers between them.
## Initiative Spectrum
Interactions sit on a spectrum:
- **User-driven**: The user gives instructions, the AI executes. The user controls pace, direction, and scope.
- **AI-driven**: The AI leads — asking questions, making suggestions, guiding the user through a process.
- **Shared**: Both parties contribute. The AI proposes, the user edits. The user starts, the AI finishes.
Most AI products default to user-driven. The interesting design space is in shared and AI-driven modes.
## Designing Initiative Handoffs
The moment control shifts from one party to the other is where most interactions fail. Design these transitions:
- **Explicit handoff**: "I've drafted three options. Which direction do you want to go?" — the AI clearly passes control.
- **Implicit handoff**: The AI stops generating and waits, signalling the user's turn through UI affordance.
- **Negotiated handoff**: "I could take this further or stop here for your input. What do you prefer?"
- **Forced handoff**: The AI encounters a decision it can't make and must hand back to the human.
## When the AI Should Lead
The AI should take initiative when:
- The user is uncertain or exploring and needs guidance
- The task has a known best-practice sequence the AI can walk through
- The user has explicitly asked for help or coaching
- Proactive suggestions would save time without being intrusive
## When the User Should Lead
The user should retain control when:
- The task involves subjective judgment or creative direction
- Stakes are high and errors are costly
- The user has strong domain expertise

…

Evidence boundary and execution chain

Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.

sections -> Initiative Spectrum → Designing Initiative Handoffs → When the AI Should Lead → When the User Should Lead → Anti-Patterns → Design Artefacts
terms    -> User-driven · AI-driven · Shared · Explicit handoff · Implicit handoff · Negotiated handoff · Forced handoff · Initiative whiplash
files/cmd -> no explicit files or commands
body sha256 -> ae69c0b6e67b