> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fish.audio/llms.txt
> Use this file to discover all available pages before exploring further.
# Post-call Analysis
> Automatic summaries, structured data extraction, and success evaluation after every conversation
After a conversation ends, the platform runs an LLM pass over the [stored transcript](/agents/monitor/conversation-history#what-gets-stored) and produces three results: a **summary**, values for the **data fields** you define, and a verdict for each **success criterion**. Summaries are on by default for every agent — extraction and evaluation are opt-in, configured per agent on the Builder's **Analysis** page.
End a preview call and watch the analysis card fill in.
Analysis is embedded in every session detail response.
Get notified the moment a conversation is analyzed.
## What a run produces
### Summary
A concise recap of the conversation. Enabled by default — every conversation gets one out of the box.
* **Custom prompt** (optional, up to 1,000 characters) — replace the platform's default summary instruction with your own, e.g. "Summarize in two sentences, focusing on the caller's request and the outcome."
* **Output language** — fixed per agent, chosen from 10 locales (English, Chinese, Japanese, Korean, Spanish, French, German, Portuguese, Russian, Arabic). Default is English.
The summary language does **not** follow the conversation language. Summaries
and rationales are always written in the configured language, even when the
conversation happened in another one — so downstream systems see consistent
output.
### Data fields
Structured values extracted from the transcript — up to **20 fields** per agent. Each field is:
| Property | Description |
| -------------- | ---------------------------------------------------------------------------------------------------------- |
| `name` | Unique per agent; lowercase letters, digits, and underscores, starting with a letter (up to 64 characters) |
| `type` | `boolean`, `text`, `number`, or `enum` |
| `description` | Instruction telling the model what to extract (up to 500 characters) |
| `enum_options` | For `enum` fields only: 2–20 allowed values |
When the conversation doesn't contain the information, the field's value is `null` with a rationale explaining why — the model never guesses.
### Success criteria
Up to **10 criteria** per agent, each a `name` plus a `description` (up to 500 characters) stating what a successful conversation looks like — "The agent resolved the caller's issue or set clear next steps."
Every criterion gets a three-state verdict with a rationale:
* **`success`** — the transcript shows the expectation was met.
* **`failure`** — the transcript shows it was not.
* **`unknown`** — the transcript is incomplete, the answer was ambiguous, or the information needed to judge is missing.
The `unknown` state is deliberate: rather than forcing an ambiguous call into
a binary verdict, the model tells you it couldn't judge — so your success-rate
numbers stay honest.
## Configure analysis
Open your agent's **Analysis** page in the Builder. Three cards — Summary, Data fields, and Criteria — autosave to the draft as you edit. You can also set the `analysis` section of the configuration via the API:
```bash theme={null}
curl --request PATCH "https://api.fish.audio/v1/agent/agents/$AGENT_ID/config" \
--header "Authorization: Bearer $FISH_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"analysis": {
"summary": { "enabled": true, "language": "en" },
"data_fields": [
{
"name": "callback_requested",
"type": "boolean",
"description": "Did the caller ask to be called back?"
},
{
"name": "issue_category",
"type": "enum",
"description": "The main topic of the call.",
"enum_options": ["billing", "shipping", "product", "other"]
}
],
"criteria": [
{
"name": "issue_resolved",
"description": "The agent fully resolved the caller'\''s issue, or set clear next steps before the call ended."
}
]
}
}'
```
Like all configuration, edits land in the [draft](/agents/deploy/versions-publishing). Preview calls use the draft immediately; production sessions pick up analysis changes after you **publish**.
To disable analysis entirely, turn the summary off and leave both lists empty — conversations then finish with analysis status `skipped` and no LLM call is made.
## When analysis runs
Analysis starts automatically when a conversation ends — production sessions from any source, and preview calls when you end them. A run moves through these statuses:
| Status | Meaning |
| ----------- | ----------------------------------------------------------------------------------- |
| `queued` | Scheduled, waiting to run |
| `running` | The LLM pass is in progress |
| `completed` | Results are available |
| `skipped` | Nothing to analyze — the conversation had no user messages, or analysis is disabled |
| `error` | The run failed; no results |
Results are typically ready within seconds of the conversation ending.
Production sessions are analyzed against the agent version pinned when the
session started — editing your criteria afterwards never changes how past
conversations were judged, and each result stays attributable to the
configuration that produced it.
## Read the results
In the Builder, analysis appears in the call panel after a preview call ends. Programmatically, the [session detail](/agents/monitor/conversation-history) response embeds it under `analysis`:
```bash theme={null}
curl "https://api.fish.audio/v1/agent/sessions/$SESSION_ID" \
--header "Authorization: Bearer $FISH_API_KEY"
```
```json theme={null}
{
"analysis": {
"status": "completed",
"summary": "The caller reported a delayed order and asked for a refund. The agent confirmed the delay, issued the refund, and offered a discount on the next purchase.",
"data": [
{
"name": "callback_requested",
"type": "boolean",
"value": false,
"rationale": "The caller did not ask to be called back."
},
{
"name": "issue_category",
"type": "enum",
"value": "shipping",
"rationale": "The conversation centered on a delayed delivery."
}
],
"criteria_results": [
{
"name": "issue_resolved",
"result": "success",
"rationale": "The refund was issued and the caller confirmed they were satisfied."
}
]
}
}
```
To push results into your CRM or data warehouse as soon as they're ready, configure a [post-call webhook](/agents/monitor/webhooks) — `call.analyzed` fires as soon as the run settles, whatever the outcome, with `analysis.status` telling you which of the terminal statuses above it reached.
## Going further
Retrieve stored transcripts and session details over REST.
Deliver analysis results to your systems automatically.
Iterate on fields and criteria with instant feedback after each test call.
How draft edits roll out to production sessions.