A football answer can involve four different clocks
The scheduled kickoff describes when a match is intended to begin. Match status describes the lifecycle state recorded by the data source. Source freshness describes when normalized data last changed. Retrieval time describes when your application read it. Collapsing those concepts into one timestamp makes an agent sound more certain than its evidence allows.
Store and exchange timestamps in UTC. Convert them at the presentation boundary using a named timezone, not a fixed numeric offset that ignores daylight-saving changes. Keep the original UTC value in the evidence record so another process can reproduce the calculation. If a user omits their timezone, ask or clearly state the display assumption.
Read status before describing the match
An agent should not infer “live,” “finished,” or “postponed” from the relationship between kickoff time and the current clock. Delays, rescheduling, abandoned matches, and incomplete sources break that shortcut. Use the returned status as the fact, and treat an unfamiliar value as an explicit unknown rather than mapping it to a familiar story.
Freshness requirements depend on the question. A historical result can tolerate an older retrieval than a near-term fixture. Define a policy in code, such as a maximum age by workflow, and expose the decision to the model. The model can then say “scheduled as of this retrieval” instead of presenting cached data as an unqualified live update.
{
"starts_at_utc": "2026-08-08T15:00:00Z",
"status": "scheduled",
"source_updated_at": "2026-07-28T04:00:00Z",
"retrieved_at": "2026-07-28T05:10:00Z",
"display_timezone": "Asia/Kolkata"
}A handoff your agent can actually follow
Treat an AI agent as a planner and transformer, not as the database. Give it a narrow task, the exact resources it may call, the response fields it may quote, and a stop condition for missing data. Keep bearer credentials in the server-side tool implementation rather than in the prompt, transcript, browser, or generated source file.
The handoff below is deliberately operational. It asks for evidence before prose, makes uncertainty visible, and keeps the model inside the current football API contract. Adapt the output format to your product, but preserve the rules about stable IDs, UTC timestamps, freshness, and error handling.
Keep stored kickoff timestamps in UTC.
Return match status, source updated time, and retrieval time as separate fields.
Convert to the user’s timezone only for display and include the timezone label.
If freshness is insufficient for the question, qualify the answer.What the human reviewer still owns
Automation can verify schemas and repeatable checks, but publication and product decisions still need a person. Review the selected competition, season, team, and match IDs; confirm that the time window matches the user’s question; and read the final answer against the retrieved JSON. A fluent explanation is not evidence that the underlying call was correct.
For time-sensitive football AI, record when the source was ingested and when the agent retrieved it. If the workflow cannot establish those timestamps, qualify the result instead of presenting it as current. The same rule applies to unavailable capabilities: do not quietly substitute fixtures or results for lineups, player statistics, odds, expected goals, injuries, or live events.
- Confirm every quoted fact appears in the retained API response.
- Exercise the empty, 401, 404, 429, and 503 paths before launch.
- Keep model interpretation separate from source facts in logs and user-facing output.
- Test daylight-saving boundaries and confirm that display conversion never mutates the UTC value retained in evidence.
Continue with the contract, not a guess
Start with the public contract and coverage ledger, then move into implementation only when the capability you need is marked available. The related guide gives your next agent-first pattern without requiring an undocumented endpoint.