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Agent skill

Esg Benchmark Comparison

by OctagonAI in OctagonAI/skills

Retrieve ESG benchmark comparison metrics by sector using Octagon MCP.

MITAuto-check passed

Install Esg Benchmark Comparison

skills CLI
$ npx skills add OctagonAI/skills --skill esg-benchmark-comparison -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install OctagonAI/skills esg-benchmark-comparison --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/esg-benchmark-comparison .claude/skills/esg-benchmark-comparison && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
esg-benchmark-comparison
GitHub stars
127
Token cost
~1.2k tokens
SKILL.md length
433 words
Files
5 (incl. references)
Skills in repo
53
Repo updated
First seen
Licence
MIT

At a glance

Retrieve ESG benchmark comparison metrics by sector using Octagon MCP.

  • Works in 4 steps: Identify Analysis Parameters → Execute Query via Octagon MCP → Expected Output → …
  • Comparing ESG performance across industries
  • SKILL.md covers Prerequisites, Workflow, Example Queries and Key Benchmark Sources, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Esg Benchmark Comparison is an agent skill from OctagonAI/skills. Retrieve ESG benchmark comparison metrics by sector using Octagon MCP. Use when comparing ESG performance across industries, analyzing sector-level sustainability benchmarks, identifying ESG leaders and laggards by industry, or referencing frameworks like MSCI, S&P Global, CDP, and CSRD.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `README.md`, `marketplace.json` and `references/interpreting-results.md`).

It works with Model Context Protocol. The repository describes itself as: A collection of Claude skills for agentic financial research by Octagon. The licence is MIT.

When your agent uses it

  • Comparing ESG performance across industries
  • Analyzing sector-level sustainability benchmarks
  • Identifying ESG leaders and laggards by industry
  • Referencing frameworks like MSCI

Example prompts

  • “/esg-benchmark-comparison”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Identify Analysis Parameters
  2. Execute Query via Octagon MCP
  3. Expected Output
  4. Interpret Results

What it can do on your machine

Read from SKILL.md and the folder at commit 51e938c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Esg Benchmark Comparison loads about 1.2k tokens when it runs, and up to ~3.6k if it reads all its reference files. Until then it costs about 78 tokens; SKILL.md has 433 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~78
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from OctagonAI/skills at commit 51e938c, republished under its MIT licence (© OctagonAI). 433 words, ~1,244 tokens.

Download SKILL.mdSave it as .claude/skills/esg-benchmark-comparison/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
esg-benchmark-comparison
description
Retrieve ESG benchmark comparison metrics by sector using Octagon MCP. Use when comparing ESG performance across industries, analyzing sector-level sustainability benchmarks, identifying ESG leaders and laggards by industry, or referencing frameworks like MSCI, S&P Global, CDP, and CSRD.

ESG Benchmark Comparison

Retrieve and analyze ESG benchmark comparison metrics across sectors and industries using the Octagon MCP server.

Prerequisites

Ensure Octagon MCP is configured in your AI agent (Cursor, Claude Desktop, Windsurf, etc.). See references/mcp-setup.md for installation instructions.

Workflow

1. Identify Analysis Parameters

Determine the following before querying:

  • Fiscal Year: Target year for benchmark data (e.g., 2024, 2023)
  • Sector (optional): Specific sector to focus on (e.g., Technology, Energy, Healthcare)
  • Framework (optional): ESG framework reference (MSCI, S&P Global, CDP, CSRD)
2. Execute Query via Octagon MCP

Use the octagon-agent tool with a natural language prompt:

Retrieve ESG benchmark comparison metrics by sector for the fiscal year <YEAR>.

MCP Call Format:

json
{
  "server": "octagon-mcp",
  "toolName": "octagon-agent",
  "arguments": {
    "prompt": "Retrieve ESG benchmark comparison metrics by sector for the fiscal year 2024."
  }
}
3. Expected Output

The agent returns sector-level ESG benchmark data including:

Sector-Level Metrics:

  • Industry ESG averages and ranges
  • Top performers by sector
  • Benchmark sources (MSCI, S&P, CDP)
  • Regional variations (EU, US, APAC)

Example Response:

SectorAvg ESG ScoreTop QuartileBottom QuartileKey Metrics
Technology72.585+<55Carbon, Data Privacy
Energy48.365+<35Emissions, Transition
Healthcare68.280+<50Access, Governance
Financials65.878+<48Ethics, Climate Risk

Data Sources: octagon-companies-agent, octagon-web-search-agent

4. Interpret Results

See references/interpreting-results.md for guidance on:

  • Understanding sector benchmark ranges
  • Identifying industry leaders and laggards
  • Comparing against ESG frameworks
  • Regional benchmark variations

Example Queries

Standard Sector Benchmarks:

Retrieve ESG benchmark comparison metrics by sector for the fiscal year 2024.

Technology Sector Focus:

Retrieve ESG benchmark comparison metrics for the Technology sector for FY2024, including MSCI and S&P benchmarks.

Energy Transition Benchmarks:

Retrieve ESG benchmark comparison for Energy sector companies with focus on climate transition metrics for 2024.

Regional Comparison:

Retrieve ESG benchmark comparison metrics by sector for EU companies in fiscal year 2024.

Framework-Specific:

Retrieve CDP climate benchmark scores by sector for 2024.

Key Benchmark Sources

SourceCoverageFocus Areas
MSCI ESGGlobalOverall ESG, Industry Materiality
S&P GlobalGlobalESG Scores, Sustainability
CDPGlobalClimate, Water, Forests
SustainalyticsGlobalESG Risk Ratings
ISS ESGGlobalGovernance, Climate
CSRDEUComprehensive Disclosure
Show full SKILL.md (184 more words)Show less

Sector Benchmark Ranges

Typical ESG score ranges by sector (0-100 scale):

SectorLowAverageHighKey Materiality
Technology457090Data privacy, supply chain
Financials406585Governance, climate risk
Healthcare456888Access, ethics, governance
Consumer Staples507290Supply chain, packaging
Energy254875Emissions, transition
Utilities355580Renewable mix, emissions
Industrials355882Safety, emissions
Materials305278Pollution, resources

Analysis Tips

  1. Sector context matters: A score of 60 may be excellent in Energy but average in Technology.

  2. Materiality focus: Each sector has different material ESG issues—compare on relevant metrics.

  3. Benchmark evolution: ESG benchmarks shift over time as standards tighten; use same-year comparisons.

  4. Regional differences: EU companies often score higher due to stricter disclosure requirements.

  5. Multiple frameworks: Cross-reference MSCI, S&P, and CDP for robust benchmarking.

Use Cases

  • Sector allocation: Identify ESG-leading sectors for portfolio tilts
  • Peer benchmarking: Compare company ESG vs sector average
  • Gap analysis: Identify areas where companies underperform sector benchmarks
  • Investment screening: Set sector-relative ESG thresholds
  • Regulatory compliance: Align with CSRD and other framework requirements

© OctagonAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in skills/esg-benchmark-comparison of OctagonAI/skills.

  • SKILL.md
  • README.md
  • marketplace.json
  • references/interpreting-results.md
  • references/mcp-setup.md

Open the folder on GitHubat commit 51e938c

Compare with similar skills

Esg Benchmark Comparison next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Esg Benchmark Comparison compared with similar skills
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Esg Benchmark Comparison this skillOctagonAI/skills127—~1.2kAutomated safety check: PassMIT
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MCP Server BuildershareAI-lab/learn-claude-code78k4 repos~1.2kAutomated safety check: PassMIT
MCP Integration for Pluginsanthropics/claude-plugins-official38k11 repos~3.1kAutomated safety check: PassApache-2.0
MCP Developmentcoollabsio/coolify63k1 repos~949Automated safety check: PassMIT
Analyze Logsactivepieces/activepieces25k1 repos~1.6kAutomated safety check: PassMIT

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Works with

Questions about Esg Benchmark Comparison

What does Esg Benchmark Comparison do?

Retrieve ESG benchmark comparison metrics by sector using Octagon MCP. Esg Benchmark Comparison is an agent skill from OctagonAI/skills. Retrieve ESG benchmark comparison metrics by sector using Octagon MCP.

When should I use Esg Benchmark Comparison?

Esg Benchmark Comparison fits situations like: comparing ESG performance across industries; analyzing sector-level sustainability benchmarks; identifying ESG leaders and laggards by industry; referencing frameworks like MSCI.

How do I install Esg Benchmark Comparison in Claude Code?

Run `npx skills add OctagonAI/skills --skill esg-benchmark-comparison -a claude-code`. Or copy the skill folder (skills/esg-benchmark-comparison in OctagonAI/skills) into .claude/skills/esg-benchmark-comparison in your project. Claude Code loads it when a task matches its description.

How do I install Esg Benchmark Comparison in Codex?

Run `npx skills add OctagonAI/skills --skill esg-benchmark-comparison -a codex`. Or copy the skill folder (skills/esg-benchmark-comparison in OctagonAI/skills) into .agents/skills/esg-benchmark-comparison in your project. Codex loads it when a task matches its description.

Can I use Esg Benchmark Comparison in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add OctagonAI/skills --skill esg-benchmark-comparison -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/esg-benchmark-comparison, .gemini/skills/esg-benchmark-comparison, .github/skills/esg-benchmark-comparison and .opencode/skills/esg-benchmark-comparison in your project.

What does Esg Benchmark Comparison need to run?

SKILL.md names no scripts, command-line tools or credentials: Esg Benchmark Comparison is instructions for the agent only.

Does Esg Benchmark Comparison access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Esg Benchmark Comparison safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Esg Benchmark Comparison use?

Esg Benchmark Comparison is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Esg Benchmark Comparison use?

About 1.2k tokens (SKILL.md is roughly 5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.3k tokens, read only when the agent opens those files.

What are the alternatives to Esg Benchmark Comparison?

Skills that share tags, products or a category with Esg Benchmark Comparison: MCP Server Builder (anthropics/skills, 180k stars), MCP Server Builder (shareAI-lab/learn-claude-code, 78k stars), MCP Integration for Plugins (anthropics/claude-plugins-official, 38k stars) and MCP Development (coollabsio/coolify, 63k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Esg Benchmark Comparison?

OctagonAI (a GitHub organization) maintains it in OctagonAI/skills, which has 127 GitHub stars. The repository holds 53 skills in this directory. The repository was last updated on June 5, 2026.

Source: OctagonAI/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.