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Intent Align

Intent-alignment orchestration for OpenClaw agent teams across diverse host environments. Use when work must stay anchored to user goals while allowing flexi...

v2.0.0
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Description


name: intent-align description: "Intent-alignment orchestration for OpenClaw agent teams across diverse host environments. Use when work must stay anchored to user goals while allowing flexible execution: (1) coding with repos/PRs/issues, (2) multi-phase delivery with checkpoints, (3) multi-agent or multi-repo coordination, (4) evolving requirements needing structured re-alignment and user clarification loops."

Intent-Align v2 Core

Keep execution aligned to user intent while preserving agent autonomy.

Quick Start

  1. Read references/core-contract.md.
  2. Create alignment hub from references/alignment-hub-template.md.
  3. Run Intent Quality Gate before planning.
  4. Select adapters from references/adapters/.
  5. Execute phases with realignment and verification gates.

Workflow Contract

  1. Build intent_snapshot and run intent_lint (see core contract).
  2. Ask for strictness mode and scope overrides (project/repo/workflow/task).
  3. Resolve effective strictness by precedence: task > workflow > repo > project > default.
  4. Evaluate ambiguity action using severity + strictness + risk class.
  5. Generate phase plan and Mermaid diagram with explicit dependencies and gates.
  6. Bind available adapters through capability_matrix.
  7. Execute phase-by-phase.
  8. Before phase start, run Pre-Execution Clarification Gate.
  9. On each phase end, run verification gates (including output conformance) and update drift evidence.
  10. If intent or constraints change, apply intent_delta and re-plan only impacted phases.
  11. Close with final alignment report and open ambiguity list (if any).

Autonomy Levels

  • 1 Strict: Require user confirmation before each phase start.
  • 2 Balanced: Require user confirmation at phase end or any critical drift.
  • 3 Aggressive: Auto-continue on low drift; require confirmation on major deltas.
  • 4 Exploratory: Continue with log-only check-ins unless risk or ambiguity threshold is exceeded.

Override rule: high-risk ambiguity is never advisory-only; enforce at least soft_gate. Strictness rule: strictness mode controls whether ambiguities block or proceed with guardrails.

Required References

Adapter Selection

Use only adapters needed for the task:

If no adapter can satisfy a required capability:

  1. Generate an ad-hoc adapter spec from adapter-template.md.
  2. Add provenance metadata (created_by, created_at, environment_assumptions, tool_access_required).
  3. Validate required fields before use.
  4. Register the new adapter in capability_matrix.adapters_selected.
  5. Continue in degraded mode only if validation fails or auth/capability remains unavailable.

Anti-Bloat Rules

  • Keep core contract tool-agnostic.
  • Do not add tracker- or host-specific logic to core files.
  • Add a new adapter only for a proven capability gap.
  • Keep schemas single-source; do not duplicate fields across files.
  • Tie each new feature to one concrete failure mode and one test scenario.
  • Generate ad-hoc adapters only for current task scope; do not pre-generate broad catalogs.
  • Use canonical capability IDs first; extend only when needed via namespaced custom IDs.

Edge Cases

  • Multi-repo: maintain one hub with per-repo adapter bindings and dependency graph.
  • Non-git prototype: use local artifacts and explicit acceptance criteria checkpoints.
  • Team swarm: assign owner per phase and keep decision log in hub.

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Pricing

Free

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