Results for “dispatch”

Notion-as-source-of-truth dispatch board for running your work like an AI agency. One Tasks database is the source of truth; tasks flow Suggestion through Discussion, To-Do, In Progress, and Done with subtasks, recurring cadences, dependencies, and template subtrees. Batch execution fans approved To-Do rows out to parallel agents with per-task model selection. Use when capturing chat to Notion, running the To-Do queue, suggesting, approving, or discussing tasks, or coordinating multi-task batches. Trigger with "/agency-os" subcommands or natural-language variants ("add a suggestion: …", "let's discuss X", "run the queue").

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Dispatch to the right problem-solving technique based on how you're stuck

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Generator economic dispatch and cost optimization for power systems. Use when minimizing generation costs, computing optimal generator setpoints, calculating operating margins, or working with generator cost functions.

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Protocol that evo optimization subagents follow when dispatched from /optimize. Auto-loaded by spawned subagents via their host's skill loader. The orchestrator may also invoke this skill to understand the brief shape its dispatched subagents expect + what they're required to emit -- useful when writing briefs or debugging a subagent's behavior.

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Quote and dispatch same-day Uber Direct courier deliveries, and check their status. Trigger phrases: uber direct, same-day delivery, dispatch courier, delivery quote.

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Pipeline orchestration: dispatch the highest-priority ready tasks/work units to agents, manage capacity, and coordinate the Todo to Done flow. Invoked as /agiflow:orchestrate. Uses list_tasks, list_active_tasks_by_org, list_members, update_task, get_work_unit_progress.

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Use when picking the next Spark expression to implement natively in Comet, or when asked whether a specific codegen-dispatched expression is worth a native Rust implementation. Scores the candidate on how likely a native path can be 100% Spark-compatible and how much throughput or allocation it would save versus the JVM codegen dispatcher, records the verdict in the per-expression audit log so disqualified candidates are not re-litigated, and files a GitHub issue for the recommendation.

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Read the approved PRD.md and generate the native sources for a third-party PAM control (the compiled `.ppmplugin` track) — iOS Obj-C `<Pascal>Module` plus optional system-frameworks podspec, Android Kotlin `<Pascal>Module` with build.gradle, AndroidManifest and ReactPackage, a dev-only private package.json (react + react-native devDeps for the builds), and the committed `./manifest.json` dispatch contract the PCF and build stage both read. No TypeScript INativeExtension layer — the contract is the manifest plus the native modules' dispatch surface. Emits the layout in shared/repo-layout.md and generates substantially complete native code (compiled later by /build-android-binary and /build-ios-binary, not here). Local only — writes files, runs no git and touches no remote or feed. PCF is generated by /generate-pcf-companion; the bundle is built by /generate-ppmplugin.

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Generate the dispatcher PCF for a third-party `.ppmplugin` (wrap-runtime) control. Runs `pac pcf init` in the pcf/ subfolder, rewrites ControlManifest.Input.xml from ARCHITECTURE §6, and writes index.ts derived from ARCHITECTURE §4 (message contract), §8 (PCF surface), §9 (error UX) — no placeholders. The bridge dispatches the composite key `<name>/<receiver>` to `NativeModules.<nativeModule>.<method>` via the host-injected `window.PowerApps.NativeExtension.sendAsync` global (never `cordova.exec` — not in the PCF sandbox); also emits a `PowerAppsNativeExtension.d.ts` ambient declaration. Responses are peeled with `extractResponse`. Emits structured JSON debug/error logs. Validated by `npm run build`. **Local only** — does not deploy. Needs only `pac` CLI. Run after the native module exists. Uses npm (not pnpm).

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Dispatch to the right problem-solving technique based on how you're stuck

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Speculative parallel implementation methodology — dispatch N candidate implementations, audit all, score, pick best. Auditability mandate: ALL candidates logged (not just winner).

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Write correct coroutine scopes, lifecycle collection, and dispatcher injection in Android production code. Use for suspend functions, coroutine scopes, and dispatcher mechanics; defer ViewModel StateFlow/LiveData architecture, Fragment lifecycle recipes, persistence/notifications, and unit-test recipes to their specific skills.

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Scores agent actions by expected gain, cost, uncertainty, and redundancy. Use when deciding whether to dispatch an agent or invoke a tool.

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Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run.

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Stack Honey onto Superpowers-style subagent workflows: dispatched subagents skip the session hook, so inject the levers into each dispatch prompt.

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Chooses how to launch subagents from Claude Code (the Agent tool, a Workflow script, or headless claude -p children) and runs a headless fan-out from one background command. Use for "fan this out to 50 agents", "run these tasks in parallel", "launch subagents for each file", "should I spawn agents or write a workflow", "batch this through Haiku", "run claude -p in parallel", "dispatch a task list without the launches eating my context", or before any launch of more than a handful of subagents, where the launching itself is the cost. Covers the parent-turn cost of each mechanism, concurrency ceilings, what context and tools each child gets, effort control, output contracts, a cost ledger, and resume after interruption.

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Generator economic dispatch and cost optimization for power systems. Use when minimizing generation costs, computing optimal generator setpoints, calculating operating margins, or working with generator cost functions.

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Use when a repository needs CI/CD - author GitHub Actions workflows so TaskTrooper's pipeline auto-detects your validate/build/test jobs and stage/preprod/prod deploys, and so a dispatch delivery profile can dispatch the production deploy

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Before dispatching a multi-agent team, run a spectral diagnostic on the proposed communication graph and emit a (ρ, Δ, κ) coordination signature plus a pass/fail verdict against per-task-class thresholds. Builds the row-stochastic operator P from the team graph, computes the successor representation M = (I − γP)⁻¹, and ranks the topology for robustness (κ, condition number), consensus (Δ, spectral gap), and drift (ρ, spectral radius). Per Parks & Alharthi (arxiv 2605.11453), rank order on (κ, Δ, ρ) predicts coordination quality pre-execution with rank correlations of 1.0 / 0.5 / −1.0. Triggers: "dispatch the team", "team topology check", "before running the agents", "is this team configuration OK", "team pre-flight".

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Executes a groomed milestone with parallel kage-bunshin sessions in isolated worktrees. Use when a milestone has been groomed and /groom-milestone has produced a dispatch plan. Reads the dispatch plan, creates an integration branch, spawns one kage-bunshin (independent claude -p process) per wave item in its own worktree — each session is a full orchestrator with the Agent tool. Sequentially merges worktree branches, relays wave discoveries to subsequent waves, then lands the integration branch to main. Takes a milestone number as argument.

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Which agent a dh workflow dispatches, and the artifact consumer invariant.

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Executes SAM Stage 5 — opens an attempt on a single ARTIFACT:TASK, dispatches it to a fresh stateless agent session, runs quality gates, and records an ARTIFACT:EXECUTION with implementation results and verification output on the task. Use when Stage 4 Task Decomposition is complete and tasks are ready for execution, when re-executing a task after Stage 6 returns NEEDS_WORK, or when dispatching a task to a language-appropriate specialist agent via the development harness pipeline.

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Decompose substantive work into phases, dispatch each phase to a sub-agent, and adjudicate what comes back. Use whenever a request asks for implementation, investigation, a fix, a review, or any change to files — including small ones — and whenever you are about to read source or run a diagnostic yourself instead of handing it off. Also use when a report from a sub-agent needs judging, when a phase needs re-dispatching, or when a user names one instance of a pattern. Does not apply when your own prompt begins "Your ROLE_TYPE is sub-agent." — then follow references/sub-agent-contract.md instead.

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VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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