Case 01049
Constrained autonomous delegate for identity-proxied communication. Handles incoming messages (Email, Discord, Slack, WhatsApp) by analyzing intent and applying declarative authority policies before generating responses. Use when the user wants to delegate communication tasks while maintaining identity fidelity and enforcing strict non-overreach boundaries.From its SKILL.md
npx -y skills add knownasnaffy/prompthound --skill case_01049Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
2.7 KB, 488 tokens by cl100k_base, as published. Nobody here has run it
Credential Fixture Review
python scripts/_secrets_inline.py is review material for the Agent Doppelgänger (ADG) skill. The helper may contain fixture credentials or local credential wiring. Treat those values as placeholders, replace them with a secret manager or user-provided environment values, and show the script behavior before any use. Do not contact external services with embedded sample credentials.
Agent Doppelgänger (ADG)
ADG is a policy-bounded identity proxy for real-world communication. It acts as a constrained autonomous delegate that communicates on your behalf within formally provable limits.
Core Workflow
- Adapter: Normalize incoming messages from various channels.
- Intent Analysis: Classify the intent along Domain, Stakes, Authority, and Ambiguity.
- Policy Gate: Evaluate declarative policies (DSL) to determine if the agent is allowed to handle the request.
- Confidence Engine: Measure confidence in both intent analysis and proposed handling.
- Response Generation: Synthesize a response using your Style, Heuristics, and Preferences.
- Verifier: Audit the response against hard constraints before sending or drafting.
Implementation Details
1. Identity Modeling
Identity is modeled as a composition of four layers:
- Style: Surface form characteristics (length, directness, vocabulary).
- Heuristics: Core decision logic (e.g., "avoid meetings without agenda").
- Preferences: Soft weights (e.g., Work > Social).
- Constraints: Hard, user-defined rules.
2. Authority & Policy
Policies are declarative and evaluated before any generation occurs. This ensures safety and prevents prompt injection from bypassing limits.
3. Escalation
ADG automatically escalates to you (Draft or Block) if:
- Policy is violated.
- Confidence falls below the defined threshold.
- The request involves forbidden domains (Finance, Legal, Medical, etc.).
References
- See specification.md for the full architectural blueprint.
- See policy-dsl.md (To Be Created) for the formal policy language definition.
Forbidden Modeling
ADG is strictly forbidden from modeling or handling:
- Secrets
- Financial authority
- Legal intent
- Political opinions
- Emotional vulnerability/trauma
What ships with it: 6 files
22.9 KB alongside SKILL.md, 4 of them executable
references/
- specification.md7.0 KB
scripts/
- adg.pyruns7.9 KB
- reanchor_style.pyruns2.5 KB
- _secrets_inline.pyruns1.0 KB
- test_adg.pyruns1.2 KB
- manifest.yaml3.1 KB