agent context overflow during export the entitlement report: context limit error failed the run

TL;DR

Take the data out of the context and put it in files the agent visits in batches. The run to export the entitlement report fails because the whole review dataset, plus logs and intermediate output, is being carried in one context window. Restructure the step to process one scoped batch at a time, write results and running state to a state file after each batch, and let the agent hold only the current batch plus a compact summary. The run then scales with the review size instead of with the context limit.

agent context overflow during export the entitlement report: context limit error failed the run

Use this when

• The run fails with a context or length limit error during the work to export the entitlement report.
• Pilot runs on small samples succeed and full review runs fail.
• The workflow loads an entire export, report or membership list into the agent at once.

Not for this skill when

• A single document or record exceeds limits on its own. That needs document splitting, not batch restructuring.
• The failure is a platform API limit, not the agent context. The error source in the log tells them apart.

Steps

1. Confirm from the run log that the failure is the agent context limit and estimate what filled it, export content, prior step output or accumulated history, by checking where in the run it failed. Verify: the filling source is identified with an approximate size.
2. Move the working data for export the entitlement report into files or a small database the workflow controls, with an index the agent can query by scope instead of reading everything. Verify: the data lives outside the context with a working index.
3. Restructure the step into batches by campaign, account, group or date range, each small enough to process comfortably, with the batch list kept in a state file. Verify: the batch plan exists and each batch is independently processable.
4. After each batch, write its results and a one line status to the state file and drop the batch raw content from the agent working context before starting the next batch. Verify: a test run of three batches keeps only summaries and the current batch in context.
5. Add a resume rule that reads the state file and starts at the first incomplete batch, so a context failure or any other stop costs at most one batch of work. Verify: killing and resuming a test run continues from the right batch.
6. Run the full task to export the entitlement report in the batched design, monitor the state file progress, and reconcile the final combined output against the Okta campaign item list. Verify: the full run completes and its output reconciles with the source.
7. Record the batch size, the state file location and the summary format in the workflow notes as the standard pattern for review sized inputs. Verify: the notes describe the batched design for reuse.

Why it happens

Context windows are working memory, not storage, and review datasets grow past them quickly: one entitlement export or membership list can exceed a window before any reasoning starts. Agents then fail at a point determined by data size, which is why pilots pass and production runs die. External state, batch processing and per batch summaries are the standard cure because they make memory use constant while the workload grows, and they bring checkpointing and resumability as free side effects.

Variants and edge cases

context limit hit during export the entitlement report in agent workflow

The limit phrasing. Identify what filled the window before restructuring; history and data need different trims.

how to process a full access review export in batches with an agent

The design phrasing. State file plus batch summaries is the pattern to copy to other review steps.

agent run works on sample data but fails on full review data

The scale phrasing. A size dependent failure is a context or volume problem until proven otherwise.

Edge cases to check before closing the review cycle:

• Never assume a timed out call did nothing. Always check the Okta campaign item list before retrying a change.
• Two retries at the same settings prove nothing. Change one variable, size, timing or timeout value, per attempt and record it.
• Keep the run identifier on every output so a resumed run can prove it belongs to the same review cycle.

Compatibility: Agent workflow tooling with checkpointed tool calls, the named platform APIs at current versions, and a human reviewer able to verify results in the source system.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_MIM7UGPxxOnfO18fLN0dxg