OpenClaw first-hour walkthrough: build a Reddit-to-Airtable claims board
This walkthrough takes one OpenClaw automation end to end: it pulls posts from two Reddit feeds, filters them with an explicit rubric, writes accepted claims to Airtable, saves the workflow as a skill, and schedules it. The output is a board of model claims scraped from r/openclaw and r/hermesagent, with the sentence and the link for each.
Why split the pipeline into five stages
The shape being taught has five parts: a source that changes, a judgment you define, a destination you can see, a reusable skill, and a schedule. Keeping stages separate makes failures easier to locate — check whether RSS contained the post, whether the rubric rejected it, and whether the Airtable write preserved every field. The author notes RSS avoids both a login and a Reddit API application, which the agent surfaced on its own when asked to plan first.
Step 0 — ask for a plan before any data
Don't open with a request for data. The prompt used was essentially: describe watching what people say about new AI models in r/openclaw and r/hermesagent, keep a running board of claims, walk through it step by step, what to pull, how to judge it, where output goes, and write it up as a PDF. The response was a short PDF covering the source, filter, destination, and open questions — and it planned to use RSS.
Step 1 — pull the data and look at it
Ask for the 20 most recent posts from each feed, printing title, author, date, and first few lines of the body as a numbered list. Both feeds came back; almost everything was setup talk, "which model should I use," and image posts with no text. That's the point of looking before transforming.
Step 2 — write the judgment
Turn posts into claims, one row per claim, and show rows before writing anywhere. In the author's Sep. 22 run, Reddit returned 25 posts per feed despite the 20-post request — 50 posts total. Feed counts can vary. Eight produced claims; the other 42 named no model or made no clear positive or negative claim.
Step 3 — push it somewhere you can see
Create an Airtable base named "First hour" and a table "Model Claims," with Model and Sentiment as single-select, Summary and Full Claim as long text, and Post as a URL. Then create a token at airtable.com/create/tokens with data.records:read, data.records:write, and schema.bases:read, scoped only to that base. Put it in TOOLS.md for the initial test, never commit that file, and move it to your normal secret manager once the integration works. The first write added the eight reviewed claims; after later runs the board held 38 claims across 28 models, every row linked to its post.
Step 4 — save the steps as a skill
Turn the flow into a skill with a Claim Key built from model + post URL + summary. Create or update only; never delete. Rerunning the same input must create no duplicates. Approve the skill file before its first run, then run once and report rows created versus unchanged. The skill holds the feeds, the rubric, the destination, and the schedule.
Who it's for
Developers already using an agent to wire RSS to a structured store who want a clean five-stage template they can copy.
📖 Read the full source: r/openclaw
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