VectleSkillsintel agent froze mid 10-k comparison on huge filing batch

intel agent froze mid 10-k comparison on huge filing batch

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This skill fixes intel agents that freeze mid 10-K comparison on huge batches. Use it when batch comparisons stall or when designing comparison pipelines. It is not for small batches; the fix is pairwise streaming, per-pair outputs, checkpoints, and per-pair watchdogs.

Intel agent froze mid 10-K comparison on a huge filing batch

TL;DR

Freezing on a huge filing batch means the agent tried to compare everything at once: all filings in memory, all pairs compared, no checkpoints. The fix is pairwise streaming: compare two filings at a time, write each result, and checkpoint. The batch becomes a sequence of small jobs that cannot freeze the run.

The error

(agent froze)
intel agent froze mid 10-K comparison on huge filing batch; no output for hours

When this helps

  • an agent freezes on large comparison batches
  • 10-K comparisons never finish
  • designing batch comparison pipelines
  • adding resumability to long agent runs

When it doesn't

  • the batch is small; pairwise streaming adds needless overhead
  • comparisons need global context; pairwise loses that, use chunked global instead
  • the freeze is a deadlock bug; fix the bug, not the batching

Works with

python 3.8+ with json. No external dependencies.

Steps

1. Compare filings pairwise, never all at once

import json
filings = ["f1.htm", "f2.htm", "f3.htm", "f4.htm"]
pairs = [(filings[i], filings[i+1]) for i in range(len(filings) - 1)]
print("pairs:", pairs)
print("each pair is one small job")

Expected: A pair list. Sequential pairs bound memory and let each comparison finish independently.

2. Write each comparison result immediately

import json
result = {"pair": ["f1.htm", "f2.htm"], "delta": "revenue up"}
open("compare_f1_f2.json", "w").write(json.dumps(result))
print("result persisted before the next pair starts")

Expected: Per-pair output files. A freeze loses at most one pair, never the batch.

3. Checkpoint the batch position

import json
state = {"done_pairs": 3, "total_pairs": 20}
open("batch_state.json", "w").write(json.dumps(state))
print("resume from pair", state["done_pairs"] + 1)

Expected: A batch checkpoint. Reruns skip completed pairs.

4. Add a watchdog timeout per pair

import signal
print("wrap each pair comparison in a 300s timeout")
print("on timeout: mark the pair failed, continue with the next")

Expected: A timeout pattern. One pathological pair cannot freeze the batch; it gets marked and skipped.

Other ways people phrase this

agent froze huge filing batch

Pairwise streaming with per-pair outputs. No step holds the batch.

10-k comparison never finishes

Checkpoint per pair. Reruns resume, freezes lose one pair.

batch comparison timeout agent

Per-pair watchdogs. Mark and skip the pathological ones.

Why it happens

Comparing N filings at once is O(N) memory and unbounded time with no intermediate output. A freeze anywhere loses everything. Pairwise streaming bounds each step to two filings, persists each result, and checkpoints progress, turning one fragile batch into many small robust jobs.

Edge cases

  • Pairwise misses N-way patterns; run a synthesis pass over the pair results after.
  • Some pairs are inherently slow; the watchdog timeout needs tuning per corpus.
  • Comparison outputs should carry both accessions for traceability.
  • A failed pair deserves one retry before being marked failed permanently.
  • Comparisons needing N-way context should run the pairwise pass first, then a synthesis pass over the pair outputs.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstPlB77If3vafdnMxQYDEwQ

Published recentlyPublished Oct 11, 2026. This reminder uses publication date only; it does not mean the content was verified. Review again after Apr 9, 2027.

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intel agent froze mid 10-k comparison on huge filing batch | Vectle