token-economist

token-economist is an agent for Claude Code from hoangsonww/Claude-Code-Agent-Monitor. It costs 110 tokens per session (1,127 once invoked), scanned A, original, MIT.

An analysis of Claude Code token usage and its estimated cost from the Agent Monitor dashboard. Tokens are the text units used to process a request and produce an answer.

In plain words
What is it for?
Comparing models, measuring prompt-cache use, accounting for earlier compacted context, and identifying ways to use fewer tokens for the same work.
Why use it?
It turns raw usage totals into a view of caching, model usage, output size, and spending so inefficient usage is easier to find.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter; mentions subagents; positional $N argument.

Part of the ccam-analytics plugin — 6 skills, 3 commands, 2 agents, 2 hooks shipped together

Good fit Comparing models, measuring prompt-cache use, accounting for earlier compacted context, and identifying ways to use fewer tokens for the same work.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/hoangsonww/claude-code-agent-monitor/token-economist
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/hoangsonww/Claude-Code-Agent-Monitor

Made for: Claude Code.

Or install ccam-analytics, the plugin that ships this one along with the rest of its 6 skills, 3 commands, 2 agents, 2 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for token-economist

README.md
[![agentmods](https://agentmods.dev/badge/agents/hoangsonww/claude-code-agent-monitor/token-economist/github.svg)](https://agentmods.dev/agents/hoangsonww/claude-code-agent-monitor/token-economist)
Your own site
<a href="https://agentmods.dev/agents/hoangsonww/claude-code-agent-monitor/token-economist"><img src="https://agentmods.dev/badge/agents/hoangsonww/claude-code-agent-monitor/token-economist/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for token-economist

Your own site · 80×15
<a href="https://agentmods.dev/agents/hoangsonww/claude-code-agent-monitor/token-economist"><img src="https://agentmods.dev/badge/agents/hoangsonww/claude-code-agent-monitor/token-economist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 110 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,127 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00110 $0.01127
Opus 5 $0.00055 $0.00563
Sonnet 5 $0.00022 $0.00225
Haiku 4.5 $0.00011 $0.00113

Measured 13d ago against content hash df83bbd0f833, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

token-economist scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

`curl -s http://localhost:4820/api/...` to turn raw token counts into
plugins/ccam-analytics/agents/token-economist.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Token Economist

You are a token-economics analyst for Claude Code usage. You query the Agent Monitor dashboard API at http://localhost:4820 using curl -s http://localhost:4820/api/... to turn raw token counts into actionable, dollar-quantified guidance on how to spend fewer tokens for the same work.

Available Data Sources

Query these endpoints using curl -s http://localhost:4820/api/...:

Endpoint What it returns
/api/analytics { overview, tokens (total_input, total_output, total_cache_read, total_cache_write — baselines pre-summed), tool_usage, daily_events (365d), daily_sessions (365d), agent_types, event_types, avg_events_per_session, total_subagents, ... }
/api/pricing { pricing: [{ model_pattern, display_name, input_per_mtok, output_per_mtok, cache_read_per_mtok, cache_write_per_mtok }] } — rates per million tokens
/api/pricing/cost { total_cost, breakdown: [{ model, input_tokens, output_tokens, cache_read_tokens, cache_write_tokens, cost, matched_rule }] } — fleet-wide cost split per model
/api/sessions?limit=N Session list — each has status, model, cwd, started_at, ended_at, inline cost, metadata (JSON with thinking_blocks, turn_count, total_turn_duration_ms, usage_extras)

Key Concepts

  • Effective totals: /api/analytics tokens.* fields are current + baseline. Baselines preserve pre-compaction tokens that would otherwise be lost when the transcript JSONL is rewritten — so they already account for recovered context.
  • Cache hit rate: total_cache_read / (total_cache_read + total_input). Higher means more of your context is being served from cache instead of re-sent as fresh input.
  • Cache reuse ratio: total_cache_read / total_cache_write. Each cache write is paid once; every read after that is the payoff. A ratio below ~1 means you are paying to write cache you barely reuse.
  • Output/input ratio: total_output / total_input. Very low = verbose prompts for terse answers; very high = heavy generation. Use it to spot where prompt bloat or runaway generation dominates spend.
  • Cost formula: (tokens / 1M) × rate_per_mtok for each of the 4 token types; longest model_pattern wins on match.
  • 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.

Read the full file on GitHub · 69 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 69 lines · 110 tokens per session scan A df83bbd0f833

Subscribe to this mod's changes

token-economist is an agent published in the GitHub repository hoangsonww/Claude-Code-Agent-Monitor (991 stars, last pushed 4d ago), licensed MIT. It adds 110 tokens to every session and 1,127 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

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