weft-run

SkillDev tools

Lets your agent build and run the weft program, then report what the run produced.

Use weft-run in Claude, ChatGPT or Ahel Desktop

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Also: Claude Code · Cursor · Codex

Then ask your AI: use the weft-run skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

weft-runStart free
About this skill

COMMAND, not reference: Build and run the weft program, then report what came out. Run this when the user asks for this step by name, optionally naming node ids to target. The sixteen `weft-` reference skills beside it are things you read; this is a procedure you carry out.

What this skill tells your AI

The instructions your AI receives, as published by weavemindai/weft in tangle/cline/.cline/skills/weft-run/SKILL.md and read by Ahel’s review.

Run this project's program and report what actually came out.

  1. Read weft-running and weft-sdp. A saved example names starting parameters to run again. Node targets name where execution stops, including those nodes; --before stops before them. With no selection, run the ordinary graph roots; triggers require an explicit fire or emitted outputs.
  2. Validate before building: weft validate --file src/main.weft < src/main.weft. Fix structural errors and inspect runtime findings. Pick an existing connection with weft connect --node <id> --grant <grant>; when credentials are missing, tell the user which node needs its Connect button or weft connect in their terminal.
  3. Run weft run --detach, adding the requested selection, or weft run <example> --detach for saved parameters. Run builds automatically. For isolated inputs use --from '<node>={"port":value}', or --group '<group>={"port":value}' for a whole group. To execute one trigger, prepare with weft bake, then use --fire '<trigger>=<wake-json>'. Read the interface before choosing payloads.
  4. Inspect status with weft executions. Read weft logs <color> for failures and weft events <color> --node <id> --full for values. If suspended, inspect the question or timer and report what it needs. Historical answers are evidence for deciding a new answer.
  5. When rerunning a frozen example, leave out --seed to review current computation, then weft diff <color> example:<name> --full. Judge the result against the user's intent. A difference is neither an automatic failure nor permission to replace the accepted example. Freeze again only after accepting the new result.
  6. Report status, the requested outcomes and any failure with its node and inputs. Name the stage this run exercised and the next stage to grow. If you start calling a completed run proof of quality, write "Wait. Read the result." and inspect the values.

Signals

GitHub stars
2k
Forks
219
Last commit
Oct 2026
Advanced
Item type
skill
Key
weft-run
Source
github.com/weavemindai/weft