scienceclaw-canvas

ScienceClaw canvas orchestration

The canvas is the working surface for scientific tasks. Instead of running ad-hoc scripts, build one typed workflow graph: nodes are tools, library operators, code or llm steps; edges carry typed values (type, shape, unit). The engine executes every edit immediately and reruns only the affected nodes, so each step returns real feedback.

Procedure

1. Declare the task. Call scienceclaw_canvas(operation=open, task={...}):
   • objective: what must be computed and delivered.
   • inputs: [{name, path, format?, description?}] — each becomes a read-only load_<name> tool. Paths must lie under the configured input roots.
   • required_output: {type, shape?, unit?} of the deliverable.
   • constraints: hard, checkable conditions, each {check, value?} with check one of finite, shape, type, range, nonempty, len_eq_input, or metric ({target, column?, metric, direction, value}: an evaluator-only quality bar against a held-out file that the workflow never loads; the metric is mae|mse|rmse|smape|r2|accuracy|f1_macro|auc). Declare only constraints that the user actually requires; they are the acceptance test.
2. Read the returned context. It lists the protocol, the actions, the task's tools, the retrieved skills (routing recipes) and typed operators from the active program. Follow a retrieved skill when it fits; it is evidence, not a rule.
3. Find tools. scienceclaw_tools(operation=search, query=...) ranks the scientific library (classical toolkits and wrappers of pretrained models). operation=show prints the documentation and whether the module can run on this host; do not plan around a tool reported as unavailable.
4. Edit one step at a time. scienceclaw_canvas(operation=act, sessionId, action={...}) applies a single atomic edit (add/modify/remove node or edge). Read the execution feedback before the next edit; fix the failing node instead of rewriting the graph.
5. Verify. When the submit node is wired, call operation=replay. The workflow is re-executed from a reset state and must reproduce its output and satisfy every constraint. Then operation=finish returns the verified deliverable and the workflow.
6. Report the deliverable together with what the workflow did, the tools used and any constraint that failed. Never present an unverified result as final.

Rules

• Inputs are read through load_<name> only; never read files outside the input roots or invent data that is not in the task.
• Prefer a library tool or typed operator over reimplementing the method; pretrained wrappers need staged weights (scienceclaw_tools(operation=weights)).
• Never ask for, print or store credentials. The engine process does not receive gateway or provider keys.
• Use scienceclaw_program to see which Skills and Operators are active. When a verified session contained a real repair (a failed replay fixed by an edit), offer to learn from it with scienceclaw_evolve; see scienceclaw-evolution for the gate and rollback.