flow-making

name	flow-making
description	Turn a natural-language objective into a downloadable .flw workflow by driving the FlowCreator engine (full 83-agent catalog), then emit a canvas-loadable .flw.
metadata	{"openclaw":{"emoji":"🌊"},"tlamatini":{"runtime":"in-process","requires_tools":["execute_command","chat_agent_file_creator"],"requires_mcps":[],"budget":{"max_iterations":10,"max_seconds":900,"max_tokens":16000},"permissions":{"filesystem":{"read":["Tlamatini/agent/agents/flowcreator/**/*","Tlamatini/agent/skills_pkg/flow_making/**/*"],"write":["${input.out_path}"]},"shell":["python agent/skills_pkg/flow_making/scripts/make_flow.py","python agent/skills_pkg/flow_making/scripts/result_to_flw.py"],"network":"deny","db":"deny"},"inputs":[{"name":"objective","type":"string","required":true,"description":"One-sentence high-level goal for the flow."},{"name":"out_path","type":"string","required":true,"description":"Absolute path to write the .flw file. If the user gives no folder, default it under the Tlamatini Templates directory (TLAMATINI_TEMPLATES, e.g. <Templates>/alert.flw) — never C:\\Temp / %TEMP%."},{"name":"flow_name","type":"string","required":false,"description":"Logical flow name FlowCreator records (defaults to the out_path basename)."},{"name":"llm_model","type":"string","required":false,"description":"Ollama model FlowCreator queries (defaults to the FlowCreator template's model)."},{"name":"llm_host","type":"string","required":false,"description":"Ollama host URL (default http://localhost:11434)."}],"outputs":[{"name":"flw_path","type":"string","required":true},{"name":"agent_count","type":"integer","required":true},{"name":"connection_count","type":"integer","required":true}],"triggers":{"keywords":["flow-making","make a flow","build a flow","create a flow","create flow file","flow file",".flw","flow from objective","scaffold a flow"],"file_globs":["**/*.flw"]}}}

Flow-Making

Related (2026-07-22): FlowCreator is now ALSO a plain wrapped chat-agent, chat_agent_flowcreator — a Multi-Turn tool (no ACPX needed) that takes prompt= + flow_filename= and writes the .flw itself. This skill is the heavier, ACPX/invoke_skill-surface path that shells out to scripts/make_flow.py; the wrapped tool is the lighter one-call path. Both convert flow_result.json → .flw with the SAME result_to_flw.py logic — this skill's scripts/result_to_flw.py and the copy vendored at agent/agents/flowcreator/result_to_flw.py (so the pool subprocess can carry it) must be kept in sync. For a simple "make me a .flw from this sentence" ask, prefer chat_agent_flowcreator; use this skill when you need the scripted pipeline.

Produce a canvas-loadable .flw from ${input.objective} by wrapping the FlowCreator engine — which already encodes the full 83-agent catalog, connection contracts, and design rules in agentic_skill.md. Do NOT hand-author the .flw JSON yourself: you do not carry the agent catalog/config-key contracts in context, so a hand-written flow hallucinates agent types and will not load.

Primary path — one deterministic call

Run the shipped driver with execute_command. It copies the FlowCreator template to an isolated runtime dir, writes its config.yaml, runs FlowCreator (which queries the configured Ollama model), and converts the result to a .flw:

python agent/skills_pkg/flow_making/scripts/make_flow.py \
  --objective "${input.objective}" \
  --out "${input.out_path}" \
  --flow-name "${input.flow_name}" \
  --model "${input.llm_model}" \
  --host "${input.llm_host}"

• The path is relative to the chat process's working directory (the Tlamatini app root, where manage.py runs — same cwd execute_command uses for python manage.py ...). If a relative call ever reports "can't open file", retry with the repo-root prefix Tlamatini/agent/skills_pkg/....
• Omit --flow-name / --model / --host when the corresponding input is empty (the driver has sensible defaults).
• Use forward slashes in --out even on Windows (e.g. C:/Users/you/Desktop/Flows/alarm.flw); the driver creates the folder if it is missing.

Reading the result

On success the last stdout line is machine-readable:

agent_count=<N> connection_count=<M> flw_path=<absolute path>

Parse it and return { flw_path, agent_count, connection_count }. Tell the user to open it on the ACP designer via Open ▸ select the .flw (it auto-deploys the agents and draws the connections).

Failure handling

If the driver exits non-zero, its last stdout line begins with ERROR . Surface that message verbatim and act on the common causes — do NOT silently fabricate a .flw:

• ERROR FlowCreator timed out / Cannot reach Ollama — Ollama is not running or the model is not pulled. Ask the user to start Ollama / pull the model, or pass a different --model.
• ERROR FlowCreator: ... — the model returned an unparseable flow; retry once, then report.
• ERROR could not locate the FlowCreator template dir — pass `--template ` (the `agent/agents/flowcreator` folder) or set `TLAMATINI_FLOWCREATOR_DIR`.

Fallback — manual two-step (only if the driver is unavailable)

1. Use chat_agent_file_creator to write a config.yaml (JSON is valid YAML) into a copy of agent/agents/flowcreator/ with { "prompt": "${input.objective}", "flow_filename": "...", "llm": {"host": "...", "model": "..."} }, then execute_command: python flowcreator.py in that copy.
2. Convert its flow_result.json to the final .flw: python agent/skills_pkg/flow_making/scripts/result_to_flw.py <runtime>/flow_result.json "${input.out_path}" and read the same agent_count=… connection_count=… flw_path=… summary line.

Notes

• The .flw schema this produces is the schemaVersion-2 nodes/connections shape the canvas loader consumes; see references/flw_schema.md.
• Never mutate the FlowCreator template in place — always run from an isolated copy (the driver does this for you).