Agently Design
SkillMediaAgently-design helps your AI plan a non-trivial Agently system before the underlying APIs are written. Once added, your AI works with you on architecture that spans multiple owners, reviews the requests and prompts in your inventory, and builds in observability and auditing from the start. The outcome is a design with clear handoffs, boundaries, lifecycle, and pressure handling agreed up front.
Available today. Use it from your connected AI after setup.
No other account needed.
After adding it, describe the system you are building and who owns each part, then work with your AI to draft the architecture and request flow before writing any underlying APIs.
Then ask your AI: use the Agently Design skill
What your AI can do with it
- Design architecture that spans multiple owners
- Review your request inventory and prompts together
- Plan handoffs between model requests
- Optimize workflows and plan for lifecycle and pressure
- Set evidence and identity boundaries
- Audit the full request chain and keep the system observable
What this skill tells your AI
The instructions your AI receives, as published by agentera/agently-skills in skills/agently-design/SKILL.md and read by ahel’s review.
Use this Skill for cross-owner design and audit. It produces ownership and handoff contracts; it does not become a scheduler, TriggerFlow definition, TaskDAG, retry engine, or RuntimeEvent protocol.
Core Workflow
- State the business decisions and completion invariants.
- Classify each decision as model-owned semantic work, host-owned deterministic work, or a hybrid bounded-enum/key decision.
- Assign every decision, state, effect, and wait to one existing owner.
- Draw request-time value dependencies and execution-time event dependencies before choosing APIs.
- Combine ordered fields in one ModelRequest only when later fields need no observation created after dispatch. Split after Actions, system access, approval, artifact readback, or host computation needed by a later model decision.
- Derive each prompt/output field from an authorized consumer and declare its type, constraints, visibility, retention, and failure behavior.
- Design evidence, canonical identity joins, lifecycle, convergence, pressure, and observation before implementation.
- For an audit, reconstruct the observed topology and identify the earliest divergent node or edge rather than inferring root cause from final output.
- Hand concrete implementation to the mechanism-owning Skill.
Required Topology Contract
When Agently use and solution/process/Prompt design-review work are both known,
apply collaborative review by default. Ask the user to confirm the
scoped ModelRequest inventory and each request's responsibility before detailed
Prompt review. Use the existing topology plan, not another ledger. Route selected
request reviews to the one-design-then-confirm process in
../agently-request/references/prompt-management.md; revisit only affected
responsibilities and handoffs after a revision.
Every non-trivial linear, branching, concurrent, or looped application needs:
- an owner/invariant ledger;
- a planned node ledger with each ModelRequest or host stage and its boundary reason;
- a value/event edge ledger with exact producer, validation, and consumer;
- a production-necessity ledger for every requested node, field, and artifact.
Use small project-defined reference data at a handoff only when it enables an independent consumer, parallel development, replay, local validation, or fault localization. Mark simulated data honestly and prove that real producer output can replace it. Do not invent a universal handoff packet.
Treat a non-terminal model result as a stage-scoped contribution: it must satisfy its local contract and create observable progress, but it does not need to claim whole-task completion. Unknown or deferred work remains explicit; terminal results and irreversible effects still require full acceptance.
Read by Design Question
- Owner matrix, project layers, terminology, state/storage, and stable flow
versus submitted DAG:
references/system-boundaries.md. - ModelRequest nodes, prompt/output contracts, same-response consumption,
fan-out, joins, and
instant:references/model-request-topology.md. - Full planned-versus-observed value/signal audit:
references/execution-topology-validation.md. - TaskContext packages, TaskWorkspace/RecordStore evidence, trusted selection
keys, refs, citations, snapshots, and fail-closed joins:
references/information-and-evidence-design.md. - Concurrency, retries, repair, replan, approval, pause/resume, cancellation,
close, pressure, and planned long-form section generation:
references/lifecycle-and-pressure-design.md. - RuntimeEvents, lineage, request telemetry, model-quality review, and
experiment comparison:
references/observability-and-validation.md.
After ownership is clear:
- one request family routes to
agently-request; - Action, MCP, ExecutionResource, TaskWorkspace, RecordStore, service, or
telemetry mechanics route to
agently-runtime; - developer-owned executable orchestration routes to
agently-triggerflow; - explicit submitted TaskDAG data remains a low-frequency
agentlyadvanced reference rather than a standalone default Skill; - source-framework mapping routes to
agently-migration.
Non-Negotiable Boundaries
- Model participation alone does not justify another request. Split only for a real decision, evidence, consumer, authorization, retry, lifecycle, or parallelism boundary.
- A ModelRequest is a dispatch-time snapshot. Provisional
instantoutput may update UI or start cancelable/idempotent preparation, but cannot inject that preparation's result back into the running request. - Give the model one host-issued selection key plus relevant facts. Host code validates the offered key and reconstructs canonical ids and metadata.
- If a selection can cross cache, queue, retry, persistence, or replay, bind it to host-owned semantic-request lineage and validate freshness before lookup.
- Every model-satisfiable business rule reaches the producer before its first attempt. Deliberately hidden security or integrity gates remain host-owned and need explicit failure/terminal policy.
- Do not request hidden chain-of-thought. Keep only bounded task-specific process fields with an explicit consumer and retention contract.
Completion Gate
Before implementation, confirm that every invariant has one owner, every request boundary has a reason, every output field has an authorized consumer, every provisional path has invalidation behavior, every loop has progress and terminal rules, every cross-boundary identity has freshness/correlation, and every validation rule has a declared producer or deliberately hidden host gate.
Do not replace semantic routing, relevance, planning, or quality judgment with keywords, regex, tokenization, or local score tables. Do not add a parallel execution topology beside TriggerFlow or TaskDAG.
Signals
- GitHub stars
- 26
- Forks
- 3
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
agently-design- Source
- github.com/agentera/agently-skills