model-savings
Estimate the dollars saved by routing eligible Claude Code work to a cheaper model family, using the Agent Monitor pricing engine. Re-prices each model's token mix at the target family's rates and quantifies the delta. Uses /api/pricing (rates), /api/pricing/cost (current per-mod
Install
npx skills add https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-cost-guard/skills/model-savings
claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install hoangsonww-claude-code-agent-monitor@llmmart
git clone https://github.com/hoangsonww/Claude-Code-Agent-Monitor.git
The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole hoangsonww/claude-code-agent-monitor collection as a plugin from our marketplace. Git is the plain clone.
Skill manifest
Model Savings
Quantify how much spend you would recover by moving eligible work to a cheaper model.
Input
The user provides: $ARGUMENTS
This is the routing question — e.g. "Opus → Sonnet", "move simple work to Haiku",
or empty (analyze every premium model against the next tier down). If no target family
is named, default to proposing the next-cheaper tier per model and say so.
Data Sources
| Endpoint | Returns |
|---|---|
GET /api/pricing |
{ pricing: [{ model_pattern, display_name, input_per_mtok, output_per_mtok, cache_read_per_mtok, cache_write_per_mtok }] } — the rate card for every family |
GET /api/pricing/cost |
{ total_cost, breakdown: [{ model, input_tokens, output_tokens, cache_read_tokens, cache_write_tokens, cost, matched_rule }] } — current spend and the exact token mix per model |
GET /api/sessions?limit=200 |
Sessions with model, inline cost, and metadata (turn_count, thinking_blocks) — used to judge which work is eligible to downshift |
GET /api/analytics |
agent_types, tool_usage, total_subagents — corroborate which task types are low-complexity and safe to route cheaper |
Savings method
For each candidate model in the cost breakdown, re-price its exact token mix at the target family's rates:
cost_at_target = (input_tokens / 1M) × target.input_per_mtok
+ (output_tokens / 1M) × target.output_per_mtok
+ (cache_read_tokens / 1M) × target.cache_read_per_mtok
+ (cache_write_tokens/ 1M) × target.cache_write_per_mtok
savings = current_model_cost − cost_at_target
Pull target.*_per_mtok from /api/pricing (longest model_pattern match wins). Default rates ($/Mtok in/out/cacheRead/cacheWrite): Opus $5/$25/$0.50/$6.25, Sonnet $3/$15/$0.30/$3.75, Haiku $1/$5/$0.10/$1.25.
Eligibility — don't promise savings on work that needs the big model
Re-pricing the full token mix is the theoretical ceiling. Scope it to eligible work:
- Low-turn sessions (
metadata.turn_countsmall) and simple subagent/tool work are safe to downshift. - Heavy-reasoning sessions (many thinking_blocks, high turn counts) likely need the premium model — exclude or discount them.
- Report both the full re-price (ceiling) and an eligible-only estimate, and state the eligibility rule you applied.
Report Sections
1. Current spend by model
Table from /api/pricing/cost: each model, its 4 token counts, and current cost. Note its share of total_cost.
2. Re-priced at target family
For each candidate, show cost_at_target and savings (absolute $ and %). Make the target rate card explicit.
3. Eligible-only estimate
Apply the eligibility rule and recompute savings over just the downshiftable token mix. Show how many sessions / what share of tokens qualified.
4. Recommended routing
Rank routing moves by eligible monthly savings (descending), top 5. For each: source → target, the token mix moved, estimated $ saved, and a confidence level (high/medium/low) based on how clearly the work is low-complexity.
5. Caveats
Cheaper models may need more turns or produce more output — note that realized savings can be lower than the static re-price, and that quality-sensitive work should stay on the premium tier.
Output
Markdown tables. Currency as USD to 4 decimal places; token counts with thousands separators; rates as $/Mtok. Always present both the ceiling (full re-price) and the eligible-only estimate so the number is honest.
Files (claude-code-agent-monitor)
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agents
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openai.yaml 266 B
interface: display_name: "Model Savings" short_description: "Estimate the dollars saved by routing eligible Claude Code..." default_prompt: "Use $model-savings to inspect CCAM data and complete this workflow safely." policy: allow_implicit_invocation: false
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SKILL.md 3.9 KB
--- name: model-savings description: > Estimate the dollars saved by routing eligible Claude Code work to a cheaper model family, using the Agent Monitor pricing engine. Re-prices each model's token mix at the target family's rates and quantifies the delta. Uses /api/pricing (rates), /api/pricing/cost (current per-model spend), /api/sessions, and /api/analytics. Use when hunting for cost cuts or comparing model tiers. --- # Model Savings Quantify how much spend you would recover by moving eligible work to a cheaper model. ## Input The user provides: **$ARGUMENTS** This is the routing question — e.g. `"Opus → Sonnet"`, `"move simple work to Haiku"`, or empty (analyze every premium model against the next tier down). If no target family is named, default to proposing the next-cheaper tier per model and say so. ## Data Sources | Endpoint | Returns | |----------|---------| | `GET /api/pricing` | `{ pricing: [{ model_pattern, display_name, input_per_mtok, output_per_mtok, cache_read_per_mtok, cache_write_per_mtok }] }` — the rate card for every family | | `GET /api/pricing/cost` | `{ total_cost, breakdown: [{ model, input_tokens, output_tokens, cache_read_tokens, cache_write_tokens, cost, matched_rule }] }` — current spend and the exact token mix per model | | `GET /api/sessions?limit=200` | Sessions with `model`, inline `cost`, and `metadata` (turn_count, thinking_blocks) — used to judge which work is *eligible* to downshift | | `GET /api/analytics` | `agent_types`, `tool_usage`, `total_subagents` — corroborate which task types are low-complexity and safe to route cheaper | ## Savings method For each candidate model in the cost `breakdown`, re-price its **exact token mix** at the target family's rates: ``` cost_at_target = (input_tokens / 1M) × target.input_per_mtok + (output_tokens / 1M) × target.output_per_mtok + (cache_read_tokens / 1M) × target.cache_read_per_mtok + (cache_write_tokens/ 1M) × target.cache_write_per_mtok savings = current_model_cost − cost_at_target ``` Pull `target.*_per_mtok` from `/api/pricing` (longest `model_pattern` match wins). Default rates ($/Mtok in/out/cacheRead/cacheWrite): **Opus** $5/$25/$0.50/$6.25, **Sonnet** $3/$15/$0.30/$3.75, **Haiku** $1/$5/$0.10/$1.25. ### Eligibility — don't promise savings on work that needs the big model Re-pricing the full token mix is the *theoretical ceiling*. Scope it to **eligible** work: - Low-turn sessions (`metadata.turn_count` small) and simple subagent/tool work are safe to downshift. - Heavy-reasoning sessions (many thinking_blocks, high turn counts) likely need the premium model — exclude or discount them. - Report both the **full re-price** (ceiling) and an **eligible-only** estimate, and state the eligibility rule you applied. ## Report Sections ### 1. Current spend by model Table from `/api/pricing/cost`: each model, its 4 token counts, and current cost. Note its share of `total_cost`. ### 2. Re-priced at target family For each candidate, show `cost_at_target` and `savings` (absolute $ and %). Make the target rate card explicit. ### 3. Eligible-only estimate Apply the eligibility rule and recompute savings over just the downshiftable token mix. Show how many sessions / what share of tokens qualified. ### 4. Recommended routing Rank routing moves by eligible monthly savings (descending), top 5. For each: source → target, the token mix moved, estimated $ saved, and a confidence level (high/medium/low) based on how clearly the work is low-complexity. ### 5. Caveats Cheaper models may need more turns or produce more output — note that realized savings can be lower than the static re-price, and that quality-sensitive work should stay on the premium tier. ## Output Markdown tables. Currency as USD to 4 decimal places; token counts with thousands separators; rates as $/Mtok. Always present both the ceiling (full re-price) and the eligible-only estimate so the number is honest.
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