Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/abilityai/trinity/dd-risk-scoringnpx skills add Abilityai/trinity --skill dd-risk-scoringgit clone --depth 1 https://github.com/Abilityai/trinityWhat 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 | $0.00029 | $0.00834 |
| Opus 5 | $0.00015 | $0.00417 |
| Sonnet 5 | $0.00006 | $0.00167 |
| Haiku 4.5 | $0.00003 | $0.00083 |
Grade A, and why
dd-risk-scoring scanned grade A with 0 findings 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 3d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
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.
Risk Scoring Methodology
As the Deal Lead, you synthesize reports from 9 specialist agents into a single investment risk score. This methodology ensures consistent, defensible scoring.
Scoring Weights
| Specialist | Weight | Rationale |
|---|---|---|
| Founder/Team (dd-founder) | 20% | Team is #1 predictor of startup success |
| Technology (dd-tech) | 15% | Core IP and technical moat |
| Business Model (dd-bizmodel) | 15% | Path to profitability |
| Traction (dd-traction) | 15% | Evidence of product-market fit |
| Market (dd-market) | 15% | TAM and growth opportunity |
| Competition (dd-competitor) | 10% | Competitive positioning |
| Compliance (dd-compliance) | 5% | Regulatory risk |
| Cap Table (dd-captable) | 3% | Investor alignment |
| Legal (dd-legal) | 2% | Legal structure and IP |
Total: 100%
Calculation Formula
Overall Risk Score = Σ (specialist_score × weight)
Example:
Founder: 25 × 0.20 = 5.0
Tech: 40 × 0.15 = 6.0
BizModel: 30 × 0.15 = 4.5
Traction: 35 × 0.15 = 5.25
Market: 20 × 0.15 = 3.0
Competitor: 45 × 0.10 = 4.5
Compliance: 15 × 0.05 = 0.75
CapTable: 25 × 0.03 = 0.75
Legal: 30 × 0.02 = 0.6
--------------------------------
Overall Risk Score: 30.35
Risk Score Interpretation
| Score Range | Rating | Recommendation |
|---|---|---|
| 0-20 | Strong Invest | Exceptional opportunity, minimal risks |
| 21-35 | Invest | Good opportunity, manageable risks |
| 36-50 | Negotiate | Proceed with caution, address key risks |
| 51-70 | Pass | Too many concerns, high risk |
| 71-100 | Strong Pass | Critical issues, do not invest |
Adjustment Factors
Apply these modifiers to the calculated score:
Positive Adjustments (reduce score)
- Repeat founder with successful exit: -5
- Strategic fit with portfolio: -3
- Strong reference checks: -2
- Clear competitive moat: -3
Negative Adjustments (increase score)
- Missing key team member: +5
- Unverified core claims: +10
- Regulatory uncertainty: +5
- Customer concentration >50%: +5
- Burn rate concern: +3
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.
- 3d ago First seen · 97 lines · 29 tokens per session scan A 4ed87b3ac469
dd-risk-scoring is a skill published in the GitHub repository Abilityai/trinity (496 stars, last pushed 5d ago), licensed Apache-2.0. It adds 29 tokens to every session and 834 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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