finance-research-agent: Skill for Claude Code

.claude/skills/ethics-assessment/SKILL.md

ethics-assessment is a skill for Claude Code from sreenathvemula/finance-research-agent. It costs 138 tokens per session (1,479 once invoked), scanned B, original, Apache-2.0.

A skill for assessing whether a company fits the user's ethical-investment rules. It examines the company's actual businesses, revenue sources, conduct, controversies, alternatives, and proportionality rather than relying only on its industry label.

In plain words
What is it for?
Use it to review company business segments, governance, litigation, ratings, and reported conduct, then produce an ethical-investment assessment while leaving the final decision to the user.
Why use it?
It turns a broad ethical-investment question into a structured review based on the user's own framework and evidence about the company.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is sreenathvemula/finance-research-agent's own configuration. It tells Claude Code how to work on finance-research-agent itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything finance-research-agent configures →

Reuse

Borrowing it

Nothing to install: this file belongs to sreenathvemula/finance-research-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/sreenathvemula/finance-research-agent/main/.claude/skills/ethics-assessment/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/sreenathvemula/finance-research-agent

Made for: Claude Code.

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 ethics-assessment

README.md
[![agentmods](https://agentmods.dev/badge/skills/sreenathvemula/finance-research-agent/ethics-assessment/github.svg)](https://agentmods.dev/skills/sreenathvemula/finance-research-agent/ethics-assessment)
Your own site
<a href="https://agentmods.dev/skills/sreenathvemula/finance-research-agent/ethics-assessment"><img src="https://agentmods.dev/badge/skills/sreenathvemula/finance-research-agent/ethics-assessment/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 ethics-assessment

Your own site · 80×15
<a href="https://agentmods.dev/skills/sreenathvemula/finance-research-agent/ethics-assessment"><img src="https://agentmods.dev/badge/skills/sreenathvemula/finance-research-agent/ethics-assessment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 138 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,479 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 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 $0.00138 $0.01479
Opus 5 $0.00069 $0.00740
Sonnet 5 $0.00028 $0.00296
Haiku 4.5 $0.00014 $0.00148

Measured 10d ago against content hash a80f7c7fff2d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade B, and why

ethics-assessment scanned grade B 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 10d 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.

Strips warnings and disclaimersmediumAnti-refusal

Omitting safety caveats hides risk from the user and is a common jailbreak preamble.

- Balanced and evidenced; never moralise beyond the framework, and never convert the ethical
.claude/skills/ethics-assessment/SKILL.md · 97 lines

How it starts

The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ethics assessment

Apply the user's ethical-investment framework rigorously to a company's real businesses and conduct — not a keyword guess. The judgement and the final investment decision remain the user's; you provide a structured, evidence-based assessment.

Procedure

  1. Load the framework (source of truth). Read scripts/Ethical Investment.txt before assessing — the user may have edited it. Apply exactly the four principles and the decision framework it states (doctrine of double effect: act morally neutral/good; good effect intended not the bad; good not flowing from the bad; proportionality — plus the primary moral orientation, trajectory, alternatives and witness tests).

  2. Establish what the company actually does. business_profile (revenue mix by segment — this is what reveals whether a "diversified" company derives revenue from an excluded activity, e.g. tobacco buried inside an FMCG), company_overview "about", and search_documents for segment detail. Do NOT judge on the sector label alone.

  3. Surface conduct & controversies. search_documents on annual reports / ratings for governance and litigation; WebSearch (credible domains only) for controversies, regulatory actions, environmental/labour issues, and how the company presents itself. Include executive pay as a conduct signal: search_documents(symbol=..., doc_types=["annual_report"], query= "ratio of remuneration of directors to median employee percentage increase") — the mandatory KMP-pay-ratio-to-median-employee disclosure. A large, widening gap between leadership's raise and both the median employee's raise and actual company performance bears on proportionality/fairness; a modest, performance-linked ratio does not. Include executive pay as a conduct signal: search_documents(symbol=..., doc_types=["annual_report"], query= "ratio of remuneration of directors to median employee percentage increase") — the mandatory KMP-pay-ratio-to-median-employee disclosure. A large, widening gap between leadership's raise and both the median employee's raise and actual company performance bears on proportionality/fairness; a modest, performance-linked ratio does not. Include executive pay as a conduct signal: search_documents(symbol=..., doc_types=["annual_report"], query= "ratio of remuneration of directors to median employee percentage increase") — the mandatory KMP-pay-ratio-to-median-employee disclosure. A large, widening gap between leadership's raise and both the median employee's raise and actual company performance bears on proportionality/fairness; a modest, performance-linked ratio does not.

Read the full file on GitHub · 97 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. 10d ago First seen · 97 lines · 138 tokens per session scan B a80f7c7fff2d

Subscribe to this mod's changes

ethics-assessment is a skill published in the GitHub repository sreenathvemula/finance-research-agent (0 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 138 tokens to every session and 1,479 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it B with 1 finding (strips warnings and disclaimers). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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