This content originally appeared on DEV Community and was authored by Sridhar S
This is a submission for the Hermes Agent Challenge: Build With Hermes Agent
My Hermes Agent Couldn’t Decide Which Contracts Needed Legal Review. One Planning Layer Fixed It. 📑🤖
What I Built
While experimenting with enterprise AI agents, I noticed a common problem:
Contract reviews are painfully manual.
Vendor agreements, NDAs, MSAs, and SOWs often require legal teams to manually inspect:
- missing clauses
- unclear liabilities
- compliance gaps
- termination conditions
- SLA definitions
I wanted to see:
Can an AI agent intelligently decide what to review and when to escalate?
So I built an Enterprise Contract Intelligence Agent powered by Hermes Agent.
Instead of simply extracting text from contracts, the agent plans tasks, invokes tools, reasons through risks, and decides whether a contract actually requires legal review.
The interesting part?
My first version failed badly.
Hermes Agent was escalating almost every contract.
NDAs.
Vendor agreements.
Even low-risk contracts.
Technically the system worked.
Practically?
Completely unusable.
The issue turned out to be simple:
The agent lacked a confidence-based decision layer.
If a single clause looked risky, Hermes escalated immediately.
That created too many false positives.
So I redesigned the workflow.
Now Hermes Agent:
- Reads the uploaded contract
- Detects contract type
- Extracts clauses
- Identifies risk signals
- Calculates confidence score
- Determines escalation need
- Generates executive summary
The result:
Hermes now behaves much more like a real enterprise analyst instead of a rule-based script.
Example output:
Contract Type:
Vendor Agreement
Risk Score:
7.2/10
Issues Found:
❌ Missing termination clause
❌ SLA definition unclear
⚠ Liability section weak
Confidence:
89%
Recommendation:
Escalate to Legal Review
For low-risk contracts:
Contract Type:
NDA
Risk Score:
2.1/10
Issues Found:
✅ Confidentiality present
✅ Termination clause present
Confidence:
94%
Recommendation:
Approved
Demo
Workflow
Contract PDF
↓
Hermes Master Agent
↓
Task Planning
↓
Clause Extraction
↓
Risk Detection
↓
Confidence Scoring
↓
Compliance Check
↓
Final Recommendation
Example Agent Plan
1. Read uploaded contract
2. Identify contract type
3. Extract important clauses
4. Detect missing sections
5. Evaluate business risk
6. Calculate confidence
7. Decide escalation
(Adding screenshots/video walkthrough soon 🚀)
Code
Repository:
https://github.com/yourusername/hermes-contract-intelligence-agent
Example decision logic:
class ContractDecisionAgent:
def should_escalate(
self,
risk_score,
confidence
):
if (
risk_score > 0.7
and confidence > 0.8
):
return (
"legal_review"
)
return (
"approved"
)
My Tech Stack
- Hermes Agent
- Python
- Azure Document Intelligence
- PDFPlumber
- PyPDF
- FastAPI / Streamlit
- LangChain
- OpenAI / Azure OpenAI
How I Used Hermes Agent
Hermes Agent sits at the center of the system.
Instead of hardcoding a workflow, I used Hermes for:
1. Planning
Hermes breaks the task into smaller reasoning steps.
Example:
Read contract
↓
Determine type
↓
Extract clauses
↓
Evaluate risk
↓
Decide escalation
2. Tool Use
Hermes invokes multiple tools dynamically:
parse_pdf()
extract_clauses()
risk_detector()
compliance_checker()
summary_generator()
Different contract types require different reasoning paths, and Hermes dynamically chooses what to do next.
3. Multi-Step Reasoning
The agent doesn't just summarize documents.
It reasons through:
- missing legal clauses
- business risk
- confidence levels
- escalation decisions
This felt like a much more realistic enterprise use case for AI agents.
One big lesson from building this:
Agentic systems become useful only when they can decide what to do next, not just generate text.
That’s where Hermes Agent really stood out for me.
Thanks for reading 🚀
hermesagentchallenge #devchallenge #agents #python
This content originally appeared on DEV Community and was authored by Sridhar S
Sridhar S | Sciencx (2026-05-26T08:52:38+00:00) My AI Agent Was Escalating Every Contract. One Decision Layer Fixed It 📑🤖📑🤖. Retrieved from https://www.scien.cx/2026/05/26/my-ai-agent-was-escalating-every-contract-one-decision-layer-fixed-it-%f0%9f%93%91%f0%9f%a4%96%f0%9f%93%91%f0%9f%a4%96/
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