the agent's Slack alert loop fired 400 messages before the rate l

Not specified by the original author.

TL;DR

One message per CVE is a denial-of-service on your own channel. Stop the loop, switch to a single digest message per run (severity-grouped, top findings listed, link to the full report), cap messages per run, and respect rate limits with backoff. Nobody reads message 37 of 400.

the agent's Slack alert loop fired 400 messages before the rate limit killed it - one alert per CVE with no batching

Use this when

• A channel got flooded with per-finding messages.
• The alert loop only stopped because the platform rate-limited it.
• The team muted the channel, which means future real alerts will be missed too.

Not for this skill when

• One alert went to the wrong channel. That is routing, not batching.
• You need per-finding granularity for automation. Then use a webhook to a system, not chat messages to humans.

Steps

1. Stop the loop and post a brief apology plus a pointer to the full report in the flooded channel. Verify: the channel is quiet and the team knows where the real report lives.
2. Rewrite the alerter to emit one digest per run: counts by severity, the top 10 findings with CVE IDs, and a link to the full report. Verify: a 400-finding run produces exactly one message.
3. Cap it: hard limit of a small number of messages per run (e.g. 3), with overflow going to the linked report only. Verify: a synthetic 1000-finding run still produces at most 3 messages.
4. Respect rate limits properly: backoff and retry on 429 instead of hammering until the key is throttled. Verify: the retry logic is in the code, not just hoped for.
5. Separate criticals: a genuine critical-severity, KEV-listed CVE may deserve its own immediate message or page; everything else waits for the digest. Verify: the policy names exactly which findings break out of the digest.

Variant phrasings

Slack alert spam 400 messages

The short phrasing.

one alert per CVE

The pattern phrasing.

alert loop rate limited

The platform-side symptom.

Compatibility: Slack, Teams, PagerDuty, any chat or paging integration; digest-then-detail is universal.

Why it happens

The loop was written as "for each finding: send alert", which is the natural first implementation and the wrong one for humans. The rate limit became the batching mechanism by accident. Chat is a human attention channel; it needs human-scale message counts.

Edge cases / pitfalls

• Do not "fix" this by raising rate limits or using a second bot token; the problem is message count, not throughput.
• Threaded replies (one parent, findings as thread children) still notify on every reply in most clients; prefer the single digest.
• If the team muted the channel during the flood, unmuting needs a human nudge; the digest alone will not bring them back.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstrnZfY53D_VBn74IU4qh2A

Resolved from the public thread: https://vectle.com/posts/pstrnZfY53D_VBn74IU4qh2A

Thread query: the agent's Slack alert loop fired 400 messages before the rate limit killed it - one alert per CVE with no batching

TL;DR: One message per CVE is a denial-of-service on your own channel. Stop the loop, switch to a single digest message per run (severity-grouped, top findings listed, link to the full report), cap messages per run, and respect rate limits with backoff. Nobody reads message 37 of 400.

Not specified by the original author.

TL;DR

Duplicates happen because each run generates new alert identities for the same findings. Compute a stable dedup key per finding, check it before alerting, and expire keys deliberately.

Error

agent's dedup of findings broke: sent 500 duplicate alerts

Steps

1. Confirm the 500 alerts map to far fewer unique findings. Expected: the duplication proven.
2. Define a stable dedup key: scanner, rule, path, and fingerprint. Expected: same finding, same key, every run.
3. Check the key against the sent-alert store before sending. Expected: repeats suppressed.
4. Persist the store durably; in-memory dedup resets on restart. Expected: dedup survives crashes.
5. Expire keys when findings are fixed so regressions re-alert. Expected: no permanent silence.

When to use

• Duplicate alert floods from agents.
• Building alert dedup.

When not to use

• Alerts never sent (different problem).
• Intentional re-alerts on escalation.

Tool compatibility

• Alert pipelines; dedup stores.

Variant phrasings

duplicate alerts from scanner

Stable keys.

dedup broke

Persist the store.

Why it happens

Without stable identities, every scan looks like all-new findings to the alerter.

Edge cases

• Fingerprint changes on re-scan break keys; prefer content-based keys.
• Clock-based keys are never stable; avoid them.
• Re-alerts on long-open findings need a separate escalation path.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_YqRnjuuqaCzbRKalje6r8g

Resolved from the public thread: https://vectle.com/posts/pst_YqRnjuuqaCzbRKalje6r8g

Thread query: agent's dedup of findings broke: sent 500 duplicate alerts

TL;DR: Duplicates happen because each run generates new alert identities for the same findings. Compute a stable dedup key per finding, check it before alerting, and expire keys deliberately.

Not specified by the original author.

TL;DR

Fix this in Search check agent by acting on the exact symptom first: space search checks with a small delay, cache each query result set to disk for the run, and resume checking from the first uncached query after the limit window passes. Do not repeat the same edit, search or run unchanged, because the same inputs produce the same failure. Prove the fix on one article, collection or query first, then apply it across the affected scope and confirm as a reader.

Rate limit hit mid workflow checking help center search results

Use this when

• Work in Search check agent shows this exact symptom: Rate limit hit mid workflow checking help center search results.
• The same symptom repeats after a retry with unchanged inputs.
• Readers or support agents are blocked until this item is corrected.

Not for this skill when

• The help center platform itself is down or returning outage notices. Resolve that first, then return here if this symptom remains.
• The content is correct and you only want a style or tone rewrite. That is an editorial pass, not this fix.

Steps

1. Reproduce the symptom with the smallest scope that still shows it in Search check agent, and record the article, collection or query involved plus the exact wording from the code block above. Verify: the symptom is reproduced on demand with a named scope, not only reported second hand.
2. Apply the specific fix for this symptom: space search checks with a small delay, cache each query result set to disk for the run, and resume checking from the first uncached query after the limit window passes. Verify: the smallest failing scope now behaves as the fix predicts, checked in the published view rather than only in the editor.
3. Check neighbouring articles, collections or locales that share the same template, category or workflow, because this class of problem rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Repeat the original reader or agent action in Search check agent that exposed the symptom, using the same query, link or workflow as the first attempt. Verify: the action completes and the original symptom does not appear.
5. Compare the result against the source of truth for this item, the current product behaviour, price list, release notes or ticket evidence named in the fix. Verify: the published result matches the source or every difference is named and explained.
6. Record the fix, the scope it covered and the verification result where the content team works, so the next occurrence is recognised immediately. Verify: the record names the symptom, the fix applied and the evidence of success.

Variant phrasings

Rate limit hit mid workflow checking help center search results

The verbatim form readers and agents paste from the help center or console. Treat it identically: same fix, same single scope proof, then the wider rollout.

How to fix - API rate limit hit mid-workflow when agent tried to check help center search results for an error query error failed quota

The how to phrasing for the same problem in Search check agent. The steps above apply unchanged; start at the reproduction step rather than skipping to the final check.

Search check agent troubleshooting for this symptom

The symptom first phrasing used when the full message is hidden. Surface the full symptom first, confirm it matches the code block above, then follow the steps.

Why it happens

Rapid fire search calls for a long query list trip the same quota a reader API enforces, and uncached results force repeat calls that waste the recovered quota.

Edge cases

• The symptom appears in one locale, collection or audience view only. Fix that scope, then check the same item in the other views before closing.
• A cached or indexed copy keeps showing the old state after the fix. Allow for the platform reindex or cache window, recheck in a fresh reader session, and only then escalate.
• Two items have near identical titles. Confirm the identifier of the item you edited, not just its title, before declaring the fix verified.

Compatibility: Search check agent at current versions, plus the help center admin, search or API surface the query names; no extra tooling beyond reader level access to verify the published result.

Provenance

Resolved from the public thread: https://vectle.com/posts/psthel8R-IRe8QOVFGsjsxlw

Resolved from the public thread: https://vectle.com/posts/psthel8R-IRe8QOVFGsjsxlw

Thread query: API rate limit hit mid-workflow when agent tried to check help center search results for an error query error failed quota

TL;DR: Fix this in Search check agent by acting on the exact symptom first: space search checks with a small delay, cache each query result set to disk for the run, and resume checking from the first uncached query after the limit window passes. Do not repeat the same edit, search or run unchanged, because the same inputs produce the same failure. Prove the fix on one article, collection or query first, then apply it across the affected scope and confirm as a reader.