What the data for this category looks like
Core data for search ad keyword management comes from search ad backends, search term reports, bidding ranking data, and landing page data. Most updates occur on a daily or weekly basis. Commonly used documents include keyword lists, negative keyword tables, bid records, and search term reports. These documents typically contain fields such as keyword text, matching mode, bid amount, click volume, and conversion volume. The text length and number of fields per document vary with the size of the ad account, and there are no fixed unified format standards.
How these characteristics create constraints for context and token handling
Operational data for search ad keyword management mostly consists of structured batch documents with fixed update frequencies. Context must cover recent keyword adjustments, negative keyword filtering, and bid records to avoid missing core operational information. Single keyword lists or search term reports can have long text lengths. Full direct import will consume a large amount of tokens, so the length and scope of context must be precisely controlled. Document fields vary significantly across different accounts. Irrelevant data must be filtered to reduce invalid token usage, ensuring context only includes content relevant to the current task. Operational staff often need to compare multiple periodic reports, so context must support loading by time range to prevent cross-period data from interfering with current summary tasks.
Configuration Settings
This configuration applies to FastGPT v4.17.0
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 800–1200 token | Adapts to the single-file text length of search ad keyword lists and negative keyword tables, avoiding exceeding model token limits |
quoteMaxToken | 600 token/entry | Matches the typical text structure of a single search term report, controlling token consumption per quoted entry |
| Maximum number of context entries | Top 10 entries | Aligns with the summary scope of daily or weekly updated operational reports, covering recent core adjustment data |
| Context filtering similarity | 0.7–0.8 | Filters duplicate bid records and search term data, reducing invalid token usage |
| Single context loading limit | 5 groups per request | Matches the daily review granularity of ad optimizers, avoiding token overload from single requests |
Three Common Misconfigurations
- Symptom: Context count is set to 0 in the workflow, but historical data is still passed to the API. Cause: The global context sync switch was not turned off. Modifying only parameters within the workflow does not take effect.
- Symptom: Token limit exceeded errors trigger during summary task runs, with logs showing request tokens exceeding model limits. Cause: The
maxContextparameter value was not restricted. Full import of keyword lists leads to token overload. - Symptom: Input and output token consumption amounts cannot be distinguished, and quota correspondence cannot be verified. Cause: Token detail statistics configuration was not enabled. Only total consumption data is viewed.
How to Verify Proper Configuration
- Import a single keyword list, check the token consumption of loaded context, confirm it does not exceed the preset
maxContextvalue. - Adjust the
quoteMaxTokenparameter, import a single search term report, verify that only text fragments of compliant length are loaded. - Enable token detail statistics, run a summary task once, confirm that input and output tokens are displayed separately.
- Check the context parameters within the workflow, set them to 0 and run the task, verify that no historical conversation data is passed.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.