> Discover all available Postdom documentation from the machine-readable index: https://postdom.com/llms.txt

# Every week, Postdom tells your agent what happened.

Finished runs become comparable evidence: outcomes, measured movement, top posts, and the gaps platforms leave behind.

Postdom returns descriptive evidence. Your connected agent decides how to use it.

## Evidence goes back to work.

Postdom closes the gap between a finished run and the next planning session. Your agent gets a record it can read, compare, and carry forward.

1. **The run finishes.** Each destination keeps its outcome, timing, and failure reason when applicable.
2. **The evidence returns.** Measurements keep their source, observation time, and availability state.
3. **Your agent plans again.** It reads the completed week before proposing the next schedule.

## Zero is a result. Null is a boundary.

A missing metric should never look like bad performance. Postdom preserves the difference before the value reaches your agent.

- **Measured value:** The platform supplied a numeric value of zero. It stays zero.
- **Missing evidence:** No evidence-backed number arrived. The null and its reason stay attached.

Reasons are guaranteed for never and unverified values. Other null values may not include a reason.

## Ask at the level the decision needs.

Read one post, one account, two completed weeks, or the outcome of one approved plan.

- **One post:** All stored destination snapshots for a finished post.
- **One account:** A rolling 7-day or 30-day publication window.
- **Completed weeks:** The latest two account-local weeks, with both observed populations.
- **One plan:** Post outcomes, metric aggregates, and the top evidence-backed post.

## A ranking that shows its missing pieces.

Postdom ranks one account by one evidence-backed metric. Posts without that metric move to an excluded list with the reason.

The tested contract fixture ranks Launch week · cut 07 at 1 with 42 seconds of watch time. It excludes Launch week · cut 08 because: The latest snapshot has no evidence-backed watch_time_s value.

Null is never used as zero to manufacture a winner.

## Nine fields. Five evidence states.

Each platform exposes a different slice of the picture. Postdom keeps that source boundary visible instead of flattening every field into the same promise.

- Measurement docs: https://postdom.com/docs/measurement.md
- get_digest: https://postdom.com/docs/tools/get-digest.md
- get_performance: https://postdom.com/docs/tools/get-performance.md
- get_best_posts: https://postdom.com/docs/tools/get-best-posts.md
- Metric availability: https://postdom.com/docs/destinations/metric-availability.md

## The dashboard is no longer the last stop.

Tools such as Buffer already let agents read recent performance. Postdom’s distinction is the contract around each value: observation context, availability, population, and exclusion reason.

The same evidence is available through get_digest, get_performance, and get_best_posts, with raw Markdown documentation for agent readers.

## Questions agents and supervisors ask.

### Can an AI agent learn what worked on TikTok, Instagram Reels, YouTube Shorts, Facebook Reels, and X?

Yes. Postdom returns post, account, completed-week, and plan evidence to the connected agent. The agent can read that evidence before it proposes the next schedule.

### How does Postdom handle a metric a platform does not provide?

Postdom returns null with an availability state instead of converting the missing value to zero. Never and unverified values also carry an explicit reason.

### What performance comparisons can an agent make?

An agent can read all stored snapshots for one post, use 7-day or 30-day account windows, compare the latest two completed account-local weeks, inspect a plan outcome, and rank one account by one supported metric.

### Does Postdom recommend what my agent should post next?

No. Postdom reports descriptive evidence, populations, timing, coverage gaps, and exclusions. The connected agent decides how to use that evidence when it plans again.

### How is Postdom performance different from a social analytics dashboard?

The evidence is machine-readable and returns to the agent that plans the schedule. Every value keeps its observation context and availability state, and unsupported observations stay out of rankings.

## Give the next schedule something real to learn from.

Connect an agent, run the schedule, and return the completed week as evidence.