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Advanced Dispatcher
by
omaression
· GitHub ↗
· v1.0.1-alpha
· MIT-0
370
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Install in OpenClaw
/install advanced-dispatcher-skill
Description
Route mid-session work to the right spawned model without changing the fixed main session. Use for coding, architecture, math, algorithms, web development, b...
README (SKILL.md)
Advanced Dispatcher
Classify work, dispatch it to the best spawned model, return the result to the main session.
Non-negotiable rules
- Never use Anthropic models unless the current prompt contains
--force-claude. - Reject
--use-claude,--force-opus,--no-opus. --force-claudeis prompt-scoped, not session-scoped.- Deterministic routing over ad hoc judgment.
openai-codex/*→longcache retention.opencode-go/*→shortcache retention.- Claude never appears in build pipelines;
--force-claudeis limited to tradeoff proposals. - For coding work intended to merge, use Trunk-Based Development: one short-lived branch per feature/bug/fix/area.
- Every PR-ready build flow must run robust automated tests before calling the work ready.
- Keep git-visible diffs minimal, atomic, and limited to necessary files.
Routing table
| Domain | Model |
|---|---|
| Code & architecture | openai-codex/gpt-5.4 |
| Math & algorithms | opencode-go/glm-5 |
| Web dev & brainstorming | opencode-go/minimax-m2.5 |
| Research & long context | opencode-go/kimi-k2.5 |
| Quick scripts & formatting | openai-codex/gpt-5.3-codex-spark |
Spanning categories → route by highest-risk deliverable: architecture > math > long-context > formatting.
Tradeoff protocol
Trigger when the user compares approaches, evaluates tradeoffs, or asks "which is better."
Default proposals: opencode-go/glm-5 + openai-codex/gpt-5.3-codex
With --force-claude: anthropic/claude-sonnet-4-6 + anthropic/claude-opus-4-6
Judge (always): openai-codex/gpt-5.4
Build pipelines
Trigger on buildq:, build:, or buildx: prefix.
Pre-step: create or verify one short-lived branch for the scoped work.
buildq: (quick, 5 steps)
- plan →
gpt-5.4 - implement →
gpt-5.4 - test →
glm-5 - simplify →
gpt-5.3-codex - retest →
glm-5
build: (standard, 10 steps)
- parallel-plan-a →
gpt-5.4 - parallel-plan-b →
glm-5 - judge-plan →
gpt-5.4 - boilerplate →
gpt-5.3-codex-spark - implement →
gpt-5.4 - test →
glm-5 - simplify →
gpt-5.3-codex - retest →
glm-5 - review-resolve →
gpt-5.4 - final-test →
glm-5
buildx: (strict, 12 steps)
- parallel-plan-a →
gpt-5.4 - parallel-plan-b →
glm-5 - judge-plan →
gpt-5.4 - boilerplate →
gpt-5.3-codex-spark - implement →
gpt-5.4 - test →
glm-5 - simplify →
gpt-5.3-codex - retest →
glm-5 - review-resolve-a →
gpt-5.4 - test-a →
glm-5 - review-resolve-b →
kimi-k2.5 - final-test →
glm-5
Exit rule: do not mark the branch PR-ready until automated tests pass and the diff stays atomic.
Judge output contract
Judge-plan must emit:
- Selected architecture
- Why it won
- Project/file structure
- Implementation order
- Branch plan (name, scope boundary)
- Test plan
- PR/CI test gates
- Simplification targets
- Done criteria
For buildx:, also include:
- Risk list
- Likely failure modes
- Review checklist
Simplify contract
Must:
- Remove dead code
- Remove speculative abstractions
- Remove duplication
- Remove over-engineered interfaces
- Prefer fewer files when clarity is preserved
Must not:
- Rewrite architecture
- Add abstractions
- Expand scope
Implementation contract
dispatcher.py must produce deterministic RoutePlan objects, expose route choice + cache retention + rationale + pipeline steps, support tradeoff/buildq/build/buildx, reject empty prompts and legacy flags.
Validation checklist
- Run
test_dispatcher.py— all pass. - Smoke test tradeoff,
buildq:,build:,buildx:. - Confirm Claude unreachable without
--force-claude. - Confirm Claude never in build pipelines.
- Confirm cache retention correctness.
- Confirm judge output includes branch plan and PR/CI test gates.
Usage Guidance
This skill appears coherent and implements only routing logic (no network calls or credentials). Before installing: (1) review dispatcher.py yourself or run the included unit tests (test_dispatcher.py) to confirm behavior in your environment; (2) verify your platform enforces provider credentials and policy separately (the skill references Anthropic but does not request keys—platform will need keys to actually call those models); (3) if you are concerned about autonomous agent activity, remember autonomous invocation is allowed by default—restrict or audit skill invocation in agent policy if needed; (4) consider restricting or monitoring any use of the --force-claude flag if Anthropic usage is disallowed in your organization.
Capability Analysis
Type: OpenClaw Skill
Name: advanced-dispatcher-skill
Version: 1.0.1-alpha
The advanced-dispatcher skill is a well-structured routing and workflow management tool designed to delegate tasks to specific AI models based on domain and command triggers (e.g., build:, buildx:). The Python logic in dispatcher.py is focused on deterministic route planning and input validation, while SKILL.md provides clear operational constraints and multi-step pipeline definitions for the agent. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found; the code and instructions are entirely consistent with the stated purpose of model dispatching and software development orchestration.
Capability Assessment
Purpose & Capability
Name/description match the implementation: dispatcher.py and tests implement deterministic routing rules, tradeoff and build pipelines, and explicit refusal of legacy flags. The models referenced in the routing table are appropriate for a routing skill and there are no unexpected credentials or system access requests.
Instruction Scope
SKILL.md confines runtime behavior to classification/routing, pipeline composition, and policies about which models to prefer or forbid. It does not instruct reading files, environment variables, network endpoints, or transmitting data to third parties. The implementation enforces non-empty prompts, domain validation, and flag rejection as described.
Install Mechanism
No install spec is provided (instruction-only style). Code files are included but there are no downloads, brew/npm installs, or archive extraction. This is low-risk from an install vector perspective.
Credentials
The skill declares no required environment variables or credentials. Although it references provider-specific model IDs (openai-codex, opencode-go, anthropic), the skill only returns routing decisions and does not itself perform API calls or ask for keys, which is proportionate to its purpose.
Persistence & Privilege
always is false and the skill does not request system-wide persistence or modify other skills. Autonomous invocation is allowed (platform default) but the skill's actions are confined to returning RoutePlan objects.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install advanced-dispatcher-skill - After installation, invoke the skill by name or use
/advanced-dispatcher-skill - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1-alpha
- Expanded "Judge output contract" with a detailed list of required outputs for judge-plan, especially for `buildx:`, including risk lists and failure modes.
- Added a new "Simplify contract" section specifying what simplification steps must and must not do.
- No changes to routing rules, pipelines, or main contract logic.
- Documentation in SKILL.md is now more explicit on output expectations.
v1.0.0-alpha
Initial alpha release with structured dispatch, model selection, and build pipeline support:
- Added skill documentation (SKILL.md, README.md) and initial tests (test_dispatcher.py).
- Defined strict model routing rules with prompt-scoped Claude enablement and cache retention policies.
- Detailed routing table, tradeoff evaluation flow, and three build pipeline protocols (`buildq:`, `build:`, `buildx:`).
- Enforced minimal atomic git diffs and required automated testing before work is PR-ready.
- Centralized all contracts and step outputs for reproducible pipeline runs and validation.
v0.5.0
Advanced build pipeline routing and strict Claude isolation.
- Added structured build pipeline support for `buildq:`, `build:`, and `buildx:` prompt triggers, each with detailed, multi-step routing.
- Enforced that Claude models are never used in build pipelines, even with `--force-claude`; Claude remains exclusive to tradeoff proposal generation.
- Expanded and formalized contracts for judge and simplify steps within build workflows.
- Enhanced implementation contract and validation checklist to cover new pipeline modes and stricter model constraints.
v0.3.0
Rebuild as a stricter ClawHub-friendly dispatcher. Update routing to GPT-5.4 for code/architecture, GLM-5 for math/algorithms, Minimax M2.5 for web dev/brainstorming, Kimi K2.5 for research/long context, and GPT-5.3 Codex Spark for quick scripts/formatting. Tradeoff evaluation now uses GLM-5 + GPT-5.3-Codex with GPT-5.4 as judge, and Claude is only allowed through prompt-scoped --force-claude.
v0.2.2
- Added explicit data egress guardrails: external model dispatch now requires user consent via `--allow-external` or runtime consent.
- Updated dispatcher to block all outbound provider runs unless egress permission is given, improving privacy and compliance.
- Expanded runtime requirements section: self-hosted deploys must set provider credentials in environment variables, and `external_data_egress` is now declared in skill manifest.
- Minor: Skill trigger pattern extended to detect `--allow-external` flag. Implementation and tests revised to enforce consent requirements across all routing logic.
- Updated docs and security notes to reflect new consent and egress controls.
v0.2.1
**Changelog v0.2.1**
- Added dispatcher logic (dispatcher.py) and tests (tests/test_dispatcher.py) to the repository.
- Scoped activation: Dispatcher now triggers only on specific flags, routing, or tradeoff keywords, not on all messages.
- Updated SKILL.md to document credential needs, narrow permission usage, and explicitly limit Anthropic model usage to controlled cases.
- Code enforces dispatcher scope via new trigger matching and gating in `should_dispatch(...)` and route logic.
- Tightened security posture: No persistent writes required; permissions limited to model spawning and parallelization.
- Expanded test coverage for routing scenarios, protocol adherence, and flag/override handling.
v0.1.0
**Major upgrade: Introduces dynamic, flag-based task routing and Mixture of Experts protocols for cost-effective, granular model selection.**
- Adds granular routing logic: sub-tasks are dispatched to specialized models based on intent (coding, research, creative, utility).
- Explicit user flags (`--use-claude`, `--force-opus`, `--no-opus`) now dynamically override standard routing, enabling strict Anthropic/Opus gating.
- Implements a multi-model “Tradeoff Evaluation Protocol”: parallel model generation with cost/labor escalation only on user demand or complexity threshold.
- Introduces session transition checks, memory state handling, and repository fetch rules for improved performance and reduced context bloat.
- Robust fallback, validation, and failure modes included for resilient operation.
- Comprehensive test coverage for routing, override logic, tradeoff flows, and error handling.
Metadata
Frequently Asked Questions
What is Advanced Dispatcher?
Route mid-session work to the right spawned model without changing the fixed main session. Use for coding, architecture, math, algorithms, web development, b... It is an AI Agent Skill for Claude Code / OpenClaw, with 370 downloads so far.
How do I install Advanced Dispatcher?
Run "/install advanced-dispatcher-skill" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Advanced Dispatcher free?
Yes, Advanced Dispatcher is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Advanced Dispatcher support?
Advanced Dispatcher is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Advanced Dispatcher?
It is built and maintained by omaression (@omaression); the current version is v1.0.1-alpha.
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