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Get Started Free →Map allegations to contract language and draft a response letter with no unintended admissions.
.claude/skills/cowork-os-legal-demand-letter-response-draft/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 14% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -6% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 20% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 7% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 67% | 0% |
Map allegations to contract language and draft a response letter with no unintended admissions.
| Name | Type | Required | Description | |---|---|---|---| | agreement_path | string | No | Optional explicit path to the governing contract | | demand_letter_path | string | No | Optional explicit path to the demand letter | | facts_path | string | No | Optional chronology/facts memo path | | client_role | select | No | Role of your client in the dispute | | response_output_path | string | No | Where to write the draft response letter | | issues_table_output_path | string | No | Where to write the allegation mapping table |
../legal-demand-letter-response-draft.json.| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 37,271 | 20,831 | -44% | 1 | 1 | 0% | 3,175 | 3,605 | +14% | 0 | 0 | — |
case-02 | pass→pass | 14,219 | 13,165 | -7% | 1 | 1 | 0% | 2,006 | 2,392 | +19% | 0 | 0 | — |
case-03 | fail→fail | 12,751 | 15,833 | +24% | 1 | 1 | 0% | 1,935 | 2,778 | +44% | 0 | 0 | — |
case-04 | fail→pass | 18,685 | 14,318 | -23% | 1 | 1 | 0% | 2,751 | 2,587 | -6% | 0 | 0 | — |
case-05 | pass→fail | 21,727 | 20,889 | -4% | 1 | 1 | 0% | 3,236 | 3,746 | +16% | 0 | 0 | — |
case-14 | pass→pass | 19,690 | 19,046 | -3% | 1 | 1 | 0% | 2,958 | 3,331 | +13% | 0 | 0 | — |
case-06 | fail→pass | 13,231 | 13,563 | +3% | 1 | 1 | 0% | 1,906 | 2,296 | +20% | 0 | 0 | — |
case-07 | fail→pass | 20,072 | 18,950 | -6% | 1 | 1 | 0% | 2,886 | 3,101 | +7% | 0 | 0 | — |
case-08 | pass→pass | 12,279 | 14,680 | +20% | 1 | 1 | 0% | 1,939 | 2,660 | +37% | 0 | 0 | — |
case-09 | fail→pass | 9,801 | 15,093 | +54% | 1 | 1 | 0% | 1,553 | 2,590 | +67% | 0 | 0 | — |
case-10 | pass→pass | 16,649 | 20,642 | +24% | 1 | 1 | 0% | 2,501 | 3,406 | +36% | 0 | 0 | — |
case-11 | fail→pass | 13,919 | 18,927 | +36% | 1 | 1 | 0% | 2,078 | 3,099 | +49% | 0 | 0 | — |
case-12 | fail→pass | 12,666 | 18,020 | +42% | 1 | 1 | 0% | 1,805 | 3,076 | +70% | 0 | 0 | — |
case-13 | fail→fail | 12,694 | 17,367 | +37% | 1 | 1 | 0% | 1,810 | 2,905 | +60% | 0 | 0 | — |
case-15 | pass→pass | 13,777 | 14,675 | +7% | 1 | 1 | 0% | 2,128 | 2,753 | +29% | 0 | 0 | — |
case-16 | pass→pass | 12,212 | 13,946 | +14% | 1 | 1 | 0% | 1,955 | 2,478 | +27% | 0 | 0 | — |
case-17 | fail→pass | 13,045 | 16,901 | +30% | 1 | 1 | 0% | 1,983 | 2,815 | +42% | 0 | 0 | — |
case-18 | pass→pass | 12,753 | 10,510 | -18% | 1 | 1 | 0% | 2,019 | 1,982 | -2% | 0 | 0 | — |
case-19 | pass→pass | 12,401 | 17,410 | +40% | 1 | 1 | 0% | 1,845 | 2,831 | +53% | 0 | 0 | — |
case-20 | pass→pass | 10,291 | 12,239 | +19% | 1 | 1 | 0% | 1,718 | 2,316 | +35% | 0 | 0 | — |
case-21 | pass→pass | 14,595 | 17,416 | +19% | 1 | 1 | 0% | 2,528 | 3,400 | +34% | 0 | 0 | — |
case-22 | pass→pass | 10,983 | 7,198 | -34% | 1 | 1 | 0% | 1,962 | 1,639 | -16% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +32 percentage points is the difference between those two pass rates over the 22 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.