cost-efficiency-analyzer

cost-efficiency-analyzer is a skill for Claude Code, Codex from awslabs/agentcore-samples. It costs 98 tokens per session (1,185 once invoked), scanned A, original, Apache-2.0.

A financial analysis tool that examines a company’s cost of goods sold, operating expenses, profit margins, and spending ratios using profit-and-loss data.

In plain words
What is it for?
Use it to review costs for a quarter, compare periods, calculate gross margin and expense ratios, and identify cost-control concerns.
Why use it?
It shows where revenue is being consumed and helps explain weakening margins or inefficient spending through comparisons over time and against benchmarks.

Skill for Claude CodeCodex ✓ vendor

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to review costs for a quarter, compare periods, calculate gross margin and expense ratios, and identify cost-control concerns.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/awslabs/agentcore-samples/cost-efficiency-analyzer
About the project

Amazon Bedrock AgentCore Samples is a collection of examples and tutorials for deploying and operating AI agents with Amazon Bedrock AgentCore. Developers use it to integrate agent applications built with different frameworks and language models while learning AgentCore features. The catalogue add-ons provide agent-oriented guidance for working with these samples and services.

awslabs/agentcore-samples · 3,457 stars · on GitHub · aws.amazon.com

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.

Any agent
npx skills add awslabs/agentcore-samples --skill cost-efficiency-analyzer
Clone the repo
git clone --depth 1 https://github.com/awslabs/agentcore-samples

Made for: Claude Code, Codex.

Wrote this? Show the measurements

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agentmods badge for cost-efficiency-analyzer

README.md
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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 cost-efficiency-analyzer

Your own site · 80×15
<a href="https://agentmods.dev/skills/awslabs/agentcore-samples/cost-efficiency-analyzer"><img src="https://agentmods.dev/badge/skills/awslabs/agentcore-samples/cost-efficiency-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 98 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,185 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00098 $0.01185
Opus 5.5 $0.00039 $0.00474
Sonnet 5.5 $0.00020 $0.00237
Haiku 4.5 $0.00010 $0.00119

Measured 1mo ago against content hash d48060aef965, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

cost-efficiency-analyzer scanned grade A with 0 findings 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 1mo 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

01-features/07-centralize-and-govern-your-ai-infrastructure/03-registry/03-advanced/strands-mcp-ecs-registry/my_skills/cost-efficiency-analyzer/SKILL.md · 105 lines

How it starts

The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Cost Efficiency Analyzer

Analyzes cost structure and operational efficiency by examining COGS, operating expenses, and their ratios relative to revenue over time.

Prerequisites

No inputs required unless the user asks about a specific quarter. Default: analyze the most recent quarter (Q3 2025) with comparison to Q2 2025.

Steps

Step 1: Fetch cost data

Fetch the quarter(s) needed:

get_financial_data(period="Q3 2025")
get_financial_data(period="Q2 2025")

If the user asks for a different quarter, fetch that instead.

Step 2: Fetch benchmarks

get_kpi_benchmarks()

Extract:

  • gross_margin_pct: formula and benchmark (40%)
  • opex_ratio: formula and benchmark (30%) — note: lower is better

Step 3: Compute cost metrics

Use python_exec to calculate cost efficiency metrics:

# Q3 2025 data
r3  = 4200000; cogs3 = 1890000; opex3 = 1050000; ebitda3 = 1260000

# Q2 2025 data (for comparison)
r2  = 3800000; cogs2 = 1710000; opex2 = 980000;  ebitda2 = 1110000

def cost_metrics(revenue, cogs, opex, ebitda, label):
    gross_profit  = revenue - cogs
    gross_margin  = round(gross_profit / revenue * 100, 1)
    cogs_pct      = round(cogs / revenue * 100, 1)
    opex_pct      = round(opex / revenue * 100, 1)
    total_cost    = cogs + opex
    total_cost_pct = round(total_cost / revenue * 100, 1)
    ebitda_margin = round(ebitda / revenue * 100, 1)
    cost_per_rev  = round(total_cost / revenue, 4)   # $ of cost per $ of revenue

    print(f"\n{label}:")
    print(f"  COGS:                ${cogs:,}  ({cogs_pct}% of revenue)")
    print(f"  Operating Expenses:  ${opex:,}  ({opex_pct}% of revenue)")
    print(f"  Total Cost:          ${total_cost:,}  ({total_cost_pct}% of revenue)")
    print(f"  Gross Margin:        {gross_margin}%  (benchmark: 40%)")
    print(f"  EBITDA Margin:       {ebitda_margin}%  (benchmark: 15%)")
    print(f"  Cost per $1 revenue: ${cost_per_rev:.4f}")
    return {"gross_margin": gross_margin, "opex_pct": opex_pct, "cogs_pct": cogs_pct,
            "total_cost_pct": total_cost_pct}

m3 = cost_metrics(r3, cogs3, opex3, ebitda3, "Q3 2025")
m2 = cost_metrics(r2, cogs2, opex2, ebitda2, "Q2 2025")

# QoQ cost efficiency change
print(f"\nQoQ Cost Efficiency Change (Q2 → Q3):")
print(f"  COGS ratio:  {m2['cogs_pct']}% → {m3['cogs_pct']}%  ({m3['cogs_pct']-m2['cogs_pct']:+.1f}pp)")
print(f"  OpEx ratio:  {m2['opex_pct']}% → {m3['opex_pct']}%  ({m3['opex_pct']-m2['opex_pct']:+.1f}pp)")
print(f"  Total cost%: {m2['total_cost_pct']}% → {m3['total_cost_pct']}%  ({m3['total_cost_pct']-m2['total_cost_pct']:+.1f}pp)")

Read the full file on GitHub · 105 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. 1mo ago First seen · 105 lines · 98 tokens per session scan A d48060aef965

Subscribe to this mod's changes

cost-efficiency-analyzer is a skill published in the GitHub repository awslabs/agentcore-samples (3,457 stars, last pushed 4d ago), licensed Apache-2.0. It adds 98 tokens to every session and 1,185 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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