cost-report

name	cost-report
description	Weekly LLM cost breakdown by provider / gateway / skill, posted to private DM
when_to_use	["Scheduled weekly","User asks \"how much am I spending?\"","After a noticeable cost spike"]
toolsets	["terminal","file"]
parameters	{"window":{"type":"string","default":"7d"},"format":{"type":"string","enum":["markdown","json","csv"],"default":"markdown"}}
security	{"trust":"trusted","notes":"Read-only over local usage logs. No untrusted input, no external writes.\n"}
model_hint	google/gemini-3.1-flash

cost-report — LLM Cost Breakdown

Generate a human-readable (or machine-readable) cost report from Hermes' usage logs.

Procedure

1. Export logs. Run:

   hermes logs export --since ${WINDOW} --format jsonl --output /tmp/hermes-logs.jsonl
   

2. Parse and aggregate. Using DuckDB (preferred) or jq + awk:

   duckdb -c "
     CREATE TABLE logs AS SELECT * FROM read_json_auto('/tmp/hermes-logs.jsonl');
     
     -- By provider
     SELECT provider,
            SUM(cost_usd) AS cost,
            SUM(tokens_in) AS tok_in,
            SUM(tokens_out) AS tok_out,
            COUNT(*) AS calls
     FROM logs
     GROUP BY 1
     ORDER BY 2 DESC;
   "
   

3. Produce four tables:

   A. By provider

   Provider     Cost($)  Tokens-in   Tokens-out   Calls
   anthropic    18.44    2.1M        380K         412
   openai       6.20     1.2M        220K         187
   cerebras     0.45     890K        140K         523
   

   B. By gateway

   Gateway     Cost($)  % of total
   telegram    14.22    56%
   cli         8.10     32%
   discord     2.77     11%
   cron        0.50     2%
   

   C. By active skill

   Skill                 Cost($)  Calls  Avg-cost
   claude-code           9.40     22     $0.43
   lightrag-query        4.11     189    $0.02
   pr-review             3.20     8      $0.40
   weekly-dep-audit      1.25     1      $1.25
   

   D. Daily trend (simple ASCII sparkline)

   Mon ▂
   Tue ▃
   Wed ▅█  ← weekly-dep-audit ran
   Thu ▃
   Fri ▄
   Sat ▂
   Sun ▁
   Total: $25.53
   

4. Flag anomalies. Use a 3x median-absolute-deviation rule on daily spend. Note any days or skills that exceed the threshold:

   ⚠ Wed spent $9.80, 4.5x typical. Driven by weekly-dep-audit.

5. Recommend savings. Pattern-match the data:

   • Any single skill > 30% of weekly cost → suggest a cheaper model for that skill
   • Input tokens > 10x output tokens on any provider → suggest prompt caching
   • Repeated Claude skills/SOUL prefixes without cache hits → enable v0.14 1-hour prefix caching
   • Gemini calls without google/gemini-3.1-flash on classification-ish intents → suggest routing
   • Grok 4.3 / GPT-5.5 / Opus calls in cron or triage lanes → require explicit opt-in routing

6. Deliver. Post to private notification channel. Attach the raw JSON if format is json.

Cron wiring

- name: weekly-cost-report
  schedule: "0 9 * * 1"
  task: /cost-report window=7d format=markdown
  notify: telegram_private

See also

• Part 20: Observability & Cost
• cost-routing playbook