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.
curl -O https://raw.githubusercontent.com/sreenathvemula/finance-research-agent/main/.claude/skills/ethics-assessment/SKILL.mdgit clone --depth 1 https://github.com/sreenathvemula/finance-research-agentWrote 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.
[](https://agentmods.dev/skills/sreenathvemula/finance-research-agent/ethics-assessment)<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.
<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>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.
| Model | Per session | Once 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 |
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 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
-
Load the framework (source of truth). Read
scripts/Ethical Investment.txtbefore 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). -
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", andsearch_documentsfor segment detail. Do NOT judge on the sector label alone. -
Surface conduct & controversies.
search_documentson 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.
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.
- 10d ago First seen · 97 lines · 138 tokens per session scan B a80f7c7fff2d
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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