use crate::classifier::ClassifyInput;
pub fn build(input: &ClassifyInput) -> String {
let recent = if input.recent_tasks.is_empty() {
"(no active tasks)".to_string()
} else {
input
.recent_tasks
.iter()
.take(10)
.map(|t| {
let trimmed_events: Vec<String> = t
.last_events
.iter()
.take(3)
.map(|s| s.chars().take(120).collect::<String>())
.collect();
format!(
"- {} \"{}\": {}",
t.task_id,
t.title,
if trimmed_events.is_empty() {
"(no events)".into()
} else {
trimmed_events.join("; ")
}
)
})
.collect::<Vec<_>>()
.join("\n")
};
format!(
"You classify chat chunks for an AI-coding-agent task journal.\n\n\
EVENT TYPE DEFINITIONS (choose the most specific match):\n\
- hypothesis: An UNVERIFIED theory or assumption (\"maybe the bug is in X\", \"I think we should try Y\"). NOT yet confirmed.\n\
- finding: A VERIFIED discovery backed by code reading or logs (\"found that function X does Y at line Z\", \"the config sets X=Y\").\n\
- evidence: Test results, benchmarks, QA outcomes, reproduction steps, logs proving something works/fails. Set evidence_strength: weak (anecdotal), medium (single test), strong (comprehensive/e2e).\n\
- decision: A chosen approach or architecture choice (\"will use strategy X because Y\"). The team commits to this.\n\
- rejection: An approach explicitly REJECTED (\"tried X but it won't work because Y\"). Important for avoiding repeated work.\n\
- constraint: An external limitation discovered (\"API rate limit is 100/min\", \"must support PHP 7.4\").\n\
- correction: The chunk CORRECTS a previous finding/hypothesis that turned out wrong. Use when the text says \"actually\", \"correction\", \"was wrong about\".\n\
- close: Task is done — fix shipped, PR merged, verified. Use when text indicates completion.\n\
- reopen: A previously closed task needs more work.\n\
- supersede: This task replaces another task entirely.\n\
- redirect: This chunk actually belongs to a different task than initially thought.\n\n\
IMPORTANT DISTINCTIONS:\n\
- hypothesis vs finding: hypothesis = \"I think\"/\"maybe\"/\"could be\"; finding = \"I see\"/\"the code shows\"/\"confirmed that\"\n\
- finding vs evidence: finding = discovered a fact; evidence = ran a test/experiment that PROVES something\n\
- decision vs hypothesis: decision = committed choice; hypothesis = exploring an option\n\n\
Active tasks (top candidates):\n{recent}\n\n\
New {author} chunk:\n{text}\n\n\
Decide:\n\
1. Which existing task this belongs to (or null if unrelated/small-talk)\n\
2. Best event_type from the definitions above\n\
3. Confidence 0.0-1.0 (0.9+ = very clear match, 0.7-0.9 = likely, <0.7 = uncertain)\n\
4. evidence_strength (weak|medium|strong) — REQUIRED if event_type is evidence, null otherwise\n\
5. A 1-2 sentence suggested_text capturing the essence. Be specific: include file names, function names, IDs when present.\n\n\
Respond ONLY with strict JSON, no commentary:\n\
{{\"event_type\":\"...\",\"task_id_guess\":\"...\"|null,\"confidence\":0.0,\"evidence_strength\":\"...\"|null,\"suggested_text\":\"...\"}}",
author=input.author_hint, text=input.text
)
}
#[cfg(test)]
mod tests {
use super::*;
use crate::classifier::*;
#[test]
fn prompt_includes_text_and_recent_tasks() {
let input = ClassifyInput {
text: "We adopted PKCE.".into(),
author_hint: "assistant".into(),
recent_tasks: vec![TaskContext {
task_id: "tj-7f3a".into(),
title: "OAuth login".into(),
last_events: vec!["[hypothesis] PKCE vs implicit".into()],
}],
};
let p = build(&input);
assert!(p.contains("We adopted PKCE."));
assert!(p.contains("tj-7f3a"));
assert!(p.contains("PKCE vs implicit"));
assert!(p.contains("strict JSON"));
}
#[test]
fn prompt_truncates_event_lines_to_keep_size_bounded() {
let input = ClassifyInput {
text: "abc".into(),
author_hint: "user".into(),
recent_tasks: (0..20)
.map(|i| TaskContext {
task_id: format!("tj-{i:03}"),
title: format!("Task {i}"),
last_events: (0..30)
.map(|j| format!("[finding] very long evidence text {i}/{j} ").repeat(20))
.collect(),
})
.collect(),
};
let p = build(&input);
assert!(
p.len() < 64 * 1024,
"prompt must stay under 64KB; got {}",
p.len()
);
}
#[test]
fn prompt_handles_empty_tasks() {
let input = ClassifyInput {
text: "Hello".into(),
author_hint: "user".into(),
recent_tasks: vec![],
};
let p = build(&input);
assert!(p.contains("(no active tasks)"));
}
}