VectleSkillsreview agent failed mid-review: ran out of tool-call budget at 200 calls on a 10-file PR: how to fix

review agent failed mid-review: ran out of tool-call budget at 200 calls on a 10-file PR: how to fix

Export

Fixes a review agent exhausting its tool-call budget by batching data fetches, capping per-file spend, and degrading gracefully instead of dying mid-review. Use when the agent burns hundreds of calls on a modest PR. Triggers: budget exhaustion, per-file fetch loops. Not for legitimately huge PRs, or retry storms multiplying a healthy budget.

TL;DR

The agent fetches data one tiny call at a time: a call per symbol, per line range, per file. Batch those into whole-file reads, cap how many calls each file may consume, and when the budget runs low, finish with a partial report instead of dying silently.

The error

review agent failed mid-review: ran out of tool-call budget at 200 calls on a 10-file PR: how to fix

Steps

1. Count calls per file from the run log

Expected output: a handful of files consume most of the 200 calls, usually through repeated small fetches.

2. Replace per-symbol lookups with whole-file reads

One file read per file, then analyze from the local copy. Expected output: call count drops by an order of magnitude for the same coverage.

3. Set a per-file call cap

Give each file a small allowance, such as 5 calls, and move on when it is spent. Expected output: one pathological file cannot starve the other nine.

4. Degrade gracefully at the global cap

When the budget runs low, stop fetching and submit what was reviewed, clearly marked as partial. Expected output: a partial review with a coverage note instead of a silent death.

5. Re-run on the same 10-file PR

Expected output: the review completes well under 200 calls.

When to use

  • The agent dies at the tool-call budget on a modest PR
  • Run logs show hundreds of small fetch calls
  • One or two files consume the whole budget

When not to use

  • Legitimately huge PRs where even batched reads exceed budget (split the PR instead)
  • Retry storms multiplying a healthy per-run budget (fix the retry loop)
  • Context-window exhaustion, which is a different limit

Tool compatibility

  • Any agentic reviewer with a tool-call budget: custom agents, coding-assistant review modes, CI review jobs
  • Whole-file reads via the git blob API, raw file endpoints, or local checkout
  • Budget accounting works the same on GitHub and GitLab hosted runners

Variant phrasings

review timed out instead of hitting a call cap

Same root cause, different limiter. Batching fixes both; also raise the timeout once the call count is sane.

context exhausted on a 10-file PR

The agent stuffed every fetch into context. Whole-file reads plus per-file caps keep context bounded too.

agent slow on large PRs but fine on small ones

Per-file cost is the lever. Cap it and the scaling curve flattens.

Why it happens

Agentic loops default to curiosity: see a symbol, fetch its definition, see another, fetch that. Each hop is a call, and hops compound across files. Without batching, a 10-file PR easily generates hundreds of calls, because the agent explores instead of reading.

Edge cases

  • One enormous generated file: exclude generated files from deep review entirely; note the skip in the summary.
  • Files that genuinely need many lookups, like a refactor touching many call sites: raise that file's cap deliberately, not the global one.
  • Partial reviews must say they are partial. A silent partial review is as bad as a silent death.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_gpVOU6xQ7tDGo8RImF0XQw

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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