VectleSkillsintel agent hit context limit, summarization failed mid 10-k run

intel agent hit context limit, summarization failed mid 10-k run

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This skill fixes intel agents that hit context limits mid 10-K summarization. Use it when prompts overflow or when designing hierarchical summarization. It is not for short filings; the fix is ITEM-section chunking, per-section summaries, summary-of-summaries synthesis, and hard character budgets.

Intel agent hit the context limit, summarization failed mid 10-K run

TL;DR

Hitting the context limit mid 10-K means the agent fed too much filing into one prompt. The fix is hierarchical summarization: summarize each ITEM section on its own, then summarize the section summaries. No prompt ever holds more than one section, so the limit becomes unreachable by construction.

The error

(agent failed)
intel agent hit context limit, summarization failed mid 10-K run; prompt exceeded max tokens

When this helps

  • an agent hits context limits on 10-Ks
  • summarization fails mid filing
  • designing hierarchical summarization
  • budgeting prompt sizes

When it doesn't

  • the filing is short; hierarchy adds needless passes
  • you need verbatim quotes; summaries lose them, extract quotes separately
  • the limit is hit by tool output, not the filing; trim the tools

Works with

python 3.8+ with re and json. Any model with a context limit.

Steps

1. Split the filing into ITEM sections

import re
htm = open("filing.htm").read()
parts = re.split(r"(?i)(ITEM\s+\d+[A-Z]?\.)", htm)
print("sections:", len(parts) // 2)
for p in parts[1::2][:6]:
    print(p[:40])

Expected: Section headings. The 10-K's own structure is the chunking scheme.

2. Summarize each section independently

import json
sections = {"ITEM 1": "business summary", "ITEM 7": "mdna summary"}
open("section_summaries.json", "w").write(json.dumps(sections, indent=2))
print("one summary per section; each prompt held one section")

Expected: Per-section summaries. The model never sees more than a section at a time.

3. Summarize the summaries for the final brief

import json
sections = json.load(open("section_summaries.json"))
combined = " ".join(sections.values())
print("synthesis input chars:", len(combined))
print("final prompt is summaries only, far under the limit")

Expected: A small synthesis input. Two levels of summarization keep every prompt bounded.

4. Enforce a per-section character budget

import json
sections = json.load(open("section_summaries.json"))
budget = 20000
for k, v in sections.items():
    sections[k] = v[:budget]
print("sections truncated to budget; no prompt can overflow")

Expected: A hard budget. Truncation at the section level guarantees the limit holds.

Other ways people phrase this

context limit 10-k summarization failed

Summarize sections, then summarize the summaries. Two levels, bounded prompts.

agent context overflow filing

Per-section budgets make overflow structurally impossible.

prompt too long 10-k agent

The filing's ITEM structure is the natural chunking.

Why it happens

10-Ks exceed every model's context window, so single-prompt summarization is doomed. Hierarchical summarization bounds each prompt to one section, and the synthesis prompt to the summaries. The context limit stops being a runtime surprise and becomes a design constant.

Edge cases

  • Section summaries lose cross-section nuance; keep key figures verbatim in the notes.
  • Very long ITEM 7s may need sub-chunking; apply the budget recursively.
  • Quote extraction should run on sections, not on summaries.
  • Track per-section token estimates; budgets need measuring, not guessing.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_Rw-Lk25t0xNEzdGQmUcbMw

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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