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llm: full per-agent usage logging with prompts and responses

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Log every model call to ~/.claude/memory/llm-logs/YYYY-MM-DD.md with
full prompt, response, agent type, model, duration, and status. One
file per day, markdown formatted for easy reading.

Agent types: fact-mine, experience-mine, consolidate, knowledge,
digest, enrich, audit. This gives visibility into what each agent
is doing and whether to adjust prompts or frequency.
This commit is contained in:
ProofOfConcept 2026-03-05 22:52:08 -05:00
parent e33fd4ffbc
commit 82b33c449c
7 changed files with 51 additions and 17 deletions
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4
src/consolidate.rs
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@ -134,7 +134,7 @@ pub fn consolidate_full_with_progress(
log_line(&mut log_buf, &format!(" Prompt: {} chars (~{} tokens)",
prompt.len(), prompt.len() / 4));
let response = match call_sonnet(&prompt, 300) {
let response = match call_sonnet("consolidate", &prompt) {
Ok(r) => r,
Err(e) => {
let msg = format!(" ERROR from Sonnet: {}", e);
@ -314,7 +314,7 @@ pub fn apply_consolidation(store: &mut Store, do_apply: bool, report_key: Option
let prompt = build_consolidation_prompt(store, &reports)?;
println!(" Prompt: {} chars", prompt.len());
let response = call_sonnet(&prompt, 300)?;
let response = call_sonnet("consolidate", &prompt)?;
let actions_value = parse_json_response(&response)?;
let actions = actions_value.as_array()