| name | REPLACE-WITH-WORKFLOW-NAME |
| description | Top-level workflow orchestrator for <use case>. Runs an end-to-end pipeline of <N> stages: <stage 1> → <stage 2> → … → <stage N>. Use when the user asks to "REPLACE-WITH-INTENT-1", "REPLACE-WITH-INTENT-2", or mentions REPLACE-WITH-DOMAIN-TERMS. Include literal trigger phrases. |
| license | Apache-2.0 |
| compatibility | Requires docker + nvidia-container-toolkit. Sub-skills declare additional requirements. |
| metadata | {"author":"REPLACE-WITH-AUTHOR-NAME","version":"0.1"} |
| allowed-tools | Read Bash |
Skill Name
High-level description of what this workflow accomplishes end-to-end.
External dependencies
Plus everything the sub-skills require — see "Related skills" below.
Related skills
This workflow invokes:
tao-skill-bank:<skill-1> —
tao-skill-bank:<skill-2> —
tao-skill-bank:<platform> — platform execution
Quick start
Default run
> Run the <workflow-name> workflow on <user-data-description>.
The orchestrator collects inputs, validates them, then dispatches the stages below.
With custom KPI / parameters
> Run the <workflow-name> workflow with KPI <metric < target>, max_iterations=3.
Resume after crash
> Resume the in-progress <workflow-name> run at <storage_root>.
State persists in <storage_root>/<state_file>.json — orchestrator reads on startup.
Inputs
| Input | Required | Description |
|---|
<input-1> | Yes | ... |
<input-2> | No | ... |
Stages
Stage 1:
- Skill:
tao-skill-bank:<skill>
- Input:
- Output:
- Condition: when this stage runs (always / conditional)
Stage 2:
(similar structure)
Storage layout
<storage_root>/
├── stage_1_output/
└── stage_2_output/
Iteration control (if applicable)
- Termination condition: KPI / metric / turn count.
- State management: how iteration N's output flows into iteration N+1.
- Checkpointing: how to resume after a crash.
Instructions
When the user asks to run this workflow, follow these steps in order:
Step 1 — Gather inputs
Confirm with the user:
<input-1>: Path / value.
<input-2>: Path / value (optional, default <value>).
Verify inputs exist:
ls <path>
Step 2 — Run the pipeline
Dispatch each stage in order. Read each sub-skill's SKILL.md for its specific invocation.
Step 3 — Report results
After completion, report metrics + output path to the user.
Known pitfalls
| Stage | Symptom | Cause | Fix |
|---|
| ... | ... | ... |