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World desk4 min

One News Bot for Bluesky and X: Why It Sends Only Five Posts a Day to X

A news bot can post broadly to Bluesky while reserving X for stories that pass an editorial source-rank threshold. The five-post result came from one day’s sample, not an X limit.
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The example news bot sends eligible stories to Bluesky, but cross-posts to X only when a story’s source OpenPageRank score is at least 6. In a one-day Renewable Energy sample, that editorial rule selected five of 34 stories—not because X limits bots to five posts a day, but because the author chose a threshold to manage relevance and cost.

How the bot chooses and routes stories

The reported setup fetches English-language Renewable Energy stories from APITube, filters for selected image-bearing stories, removes previously seen items and duplicate headlines, then limits each run to at most three new stories. Every eligible story is sent to Bluesky; a story is sent to X only if its source OpenPageRank (OPR) score is at least 6. The threshold is an editorial policy, not an objective definition of news quality.

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The implementation article, published by APITube News API on September 27, 2026, describes a sample of 270 stories collected for September 16, with measurements taken using an APITube key on September 17. After its filters and title de-duplication, 34 stories remained; five met the OPR threshold of 6. The article also reports that 23 stories had a source rank of at least 5, illustrating how changing the threshold changes the X volume. These are observations from one feed on one day, not a general daily forecast. Read the implementation article.

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Why title deduplication matters

Removing repeated URLs alone would not have cleaned this sample: all 270 hrefs were distinct, and the article says neither href deduplication nor APITube’s is_duplicate flag removed any items. Normalizing titles reduced the set to 252 unique headlines, identifying 18 repeats. Syndicated coverage can describe the same story at different URLs, so a durable bot should track both canonicalized URLs and normalized titles across runs rather than relying on links alone.

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Normalization can be as simple as lowercasing a title, trimming whitespace, and collapsing punctuation or repeated spaces before comparison. More aggressive normalization risks merging genuinely different stories; retain the original headline and URL for review, and decide how long to keep seen-item state based on the feed’s publication cadence.

What five X posts mean for cost

X’s official pay-per-usage pricing page, checked October 7, 2026, lists Post: Create at $0.015 per request and Post: Create (with URL) at $0.200 per request. The bot’s example posts links, so the higher URL rate is the relevant figure for the following illustration. X says rates can change; check the current pricing page before budgeting.

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Illustrative posting rate Calculation at $0.200 per URL post 30-day total
34 URL posts per day 34 × 30 × $0.200 $204
5 URL posts per day 5 × 30 × $0.200 $30
One post without a URL One Post: Create request $0.015 per request

The two monthly figures apply the single-day sample counts to every day of a 30-day month; they are arithmetic illustrations, not forecasts, a guaranteed bill, or an X quota. Actual usage depends on the number of posts, whether each request includes a URL, and the rates in effect when the requests are made.

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A reproducible design for a scheduled bot

  1. Fetch a narrow feed. Query the selected language and industry, then apply publication-time, image, and source-rank filters that suit the account. The APITube article describes those fields for its example; treat its feed selection as a starting configuration, not a universal prescription.
  2. Deduplicate and persist state. Compare both normalized titles and URLs against a state store that survives scheduled runs. This helps prevent repeats when the same story is syndicated under a different link or reappears in the fetch window.
  3. Cap the batch. The example uses MAX_PER_RUN = 3 and processes eligible stories in order. Its replay of the sampled day did not reach that cap, but a busier feed may. A cap limits bursts; it does not by itself guarantee a particular daily volume.
  4. Apply a platform-specific rule. Send qualifying stories to Bluesky and apply a separate X rule such as X_MIN_OPR = 6. Tune it against the feed’s observed volume and your editorial standards; the sample shows that even a small threshold change can substantially alter the number selected.
  5. Keep platform calls and content handling separate. Prepare each post once, then use each platform’s own SDK call and account credentials. The implementation article links to the AT Protocol SDK for Python and Tweepy documentation as implementation resources. Their presence does not establish that the article’s calls were validated against live accounts.
  6. Test the complete workflow cautiously. Begin with fetch, filtering, state updates, and rendered post text in a dry run. When you enable posting, verify credentials and inspect the first live result on each service before increasing automation. This is a prudent rollout approach, not a test outcome reported by the article.

Scheduling: a cron time is not a delivery promise

The example uses a GitHub Actions schedule every 30 minutes and pairs a 24-hour fetch window with persistent state. The window gives the bot a chance to find stories after a delayed run; persistent state helps avoid posting those stories again on the next run. These mechanisms mitigate missed timing, but cannot guarantee that a scheduled workflow runs exactly on time.

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GitHub’s documentation says scheduled workflows can be delayed during periods of high load and may be dropped when load is sufficiently high. A scheduled workflow must also exist on the repository’s default branch. See GitHub’s schedule event documentation when configuring the workflow. Choose an interval and lookback window that tolerate delay, and ensure your state storage remains available between runs.

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What the reported run does—and does not—validate

The author reports that fetching, deduplication, and thumbnail preparation ran live, but real Bluesky and X account posting calls were not exercised. The SDK calls are therefore implementation examples, not evidence of an end-to-end production test. The measured counts and duplicate behavior describe the reported APITube sample; they do not establish how another topic, feed, account, or posting schedule will behave.

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