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Get Started Free →Enforces a strict input boundary protocol (detect, classify, filter, verify) to ensure untrusted data never reaches business logic raw.
.claude/skills/sickn33-infinity/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-13 | ✗→✓ | ▲ Improved | 49% | 0% |
| case-01 | ✗→✓ | ▲ Improved | -11% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -3% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 35% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 38% | 0% |
> Nothing untrusted ever reaches the core — it is stopped before contact. No external data touches the codebase raw. Every boundary where data enters the system must have a filter.
The #1 source of silent bugs, crashes, and vulnerabilities is external data that arrives in an unexpected shape and gets used directly without checking. This skill enforces a filter layer at every entry point, every time.
.body, .params, .query, .env, fs.read, or a third-party SDK responseBefore writing or modifying any code that involves external data, the AI must identify and list every entry point in scope:
> The AI must not write any data-handling logic until every entry point in scope is listed.
For every entry point identified, the AI classifies it into one of three trust levels:
| Level | Definition | Examples | |---|---|---| | TRUSTED | Internal constants, hardcoded values, your own compile-time config | Enum values, hardcoded defaults, internal constants | | SEMI-TRUSTED | Your own internal services, internal APIs, controlled infrastructure | Internal microservice responses, your own database reads | | UNTRUSTED | Anything from users, the internet, third parties, or the filesystem | User input, external API responses, uploaded files, env vars, CLI args |
> Rule: TRUSTED inputs may be used directly. SEMI-TRUSTED and UNTRUSTED inputs must pass through a filter layer before any use.
The AI outputs this classification before writing any handling code:
INFINITY — BOUNDARY MAP
─────────────────────────────────────────
Entry Point | Trust Level | Filter Required
─────────────────────────────────────────
req.body.email | UNTRUSTED | ✓ format + sanitize
process.env.API_KEY | UNTRUSTED | ✓ presence + non-empty
internalService.getData()| SEMI-TRUSTED | ✓ schema validate
PAGINATION_LIMIT = 20 | TRUSTED | ✗ none needed
─────────────────────────────────────────Every UNTRUSTED and SEMI-TRUSTED input must pass through validation before it reaches any business logic, storage, or rendering. The AI must apply the right filter type for the right context:
Type Checking
Schema Validation
Sanitization
Presence & Format Checks
Rejection Rule
// WRONG — using raw input directly
const user = await db.find(req.params.id);
// RIGHT — validate before use
const id = req.params.id;
if (!id || typeof id !== 'string' || !isValidUUID(id)) {
return res.status(400).json({ error: 'Invalid ID format' });
}
const user = await db.find(id);Before the AI declares any data-handling code complete, it traces each entry point and confirms:
INFINITY — VERIFICATION
─────────────────────────────────────────
Entry Point | Filter Exists | Filter Type
─────────────────────────────────────────
req.body.email | ✓ YES | format + sanitize
process.env.API_KEY | ✓ YES | presence check
internalService.getData()| ✓ YES | schema validation
─────────────────────────────────────────
Unfiltered inputs reaching logic: NONE ✓
─────────────────────────────────────────If any UNTRUSTED or SEMI-TRUSTED input reaches logic, storage, or rendering without a filter — the AI flags it. It does not silently pass.
| Phase | Action | Writes Code? | |---|---|---| | 1 — Detect | List all entry points in scope | ❌ No | | 2 — Classify | Assign trust level to each input | ❌ No | | 3 — Filter | Write filter layer for all UNTRUSTED + SEMI-TRUSTED | ✅ Yes | | 4 — Verify | Trace each input, confirm filter exists | ❌ No |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-13 | fail→pass | 13,632 | 10,364 | -24% | 1 | 1 | 0% | 2,193 | 3,257 | +49% | 0 | 0 | — |
case-01 | fail→pass | 22,796 | 12,368 | -46% | 1 | 1 | 0% | 4,225 | 3,767 | -11% | 0 | 0 | — |
case-02 | fail→pass | 21,203 | 11,722 | -45% | 1 | 1 | 0% | 3,850 | 3,741 | -3% | 0 | 0 | — |
case-03 | fail→fail | 23,371 | 13,224 | -43% | 1 | 1 | 0% | 4,157 | 3,997 | -4% | 0 | 0 | — |
case-04 | pass→fail | 26,573 | 22,141 | -17% | 1 | 1 | 0% | 5,364 | 5,909 | +10% | 0 | 0 | — |
case-05 | pass→fail | 6,029 | 8,156 | +35% | 1 | 1 | 0% | 1,149 | 2,857 | +149% | 0 | 0 | — |
case-06 | pass→fail | 14,162 | 9,421 | -33% | 1 | 1 | 0% | 3,027 | 3,352 | +11% | 0 | 0 | — |
case-07 | fail→pass | 13,389 | 9,324 | -30% | 1 | 1 | 0% | 2,367 | 3,206 | +35% | 0 | 0 | — |
case-08 | fail→pass | 11,937 | 7,179 | -40% | 1 | 1 | 0% | 1,885 | 2,605 | +38% | 0 | 0 | — |
case-09 | pass→pass | 13,788 | 8,453 | -39% | 1 | 1 | 0% | 2,356 | 2,948 | +25% | 0 | 0 | — |
case-10 | fail→pass | 11,797 | 6,193 | -48% | 1 | 1 | 0% | 2,006 | 2,480 | +24% | 0 | 0 | — |
case-11 | pass→pass | 14,756 | 8,308 | -44% | 1 | 1 | 0% | 2,227 | 2,814 | +26% | 0 | 0 | — |
case-12 | pass→pass | 13,542 | 8,715 | -36% | 1 | 1 | 0% | 2,131 | 2,992 | +40% | 0 | 0 | — |
case-14 | fail→pass | 19,159 | 12,453 | -35% | 1 | 1 | 0% | 2,912 | 3,570 | +23% | 0 | 0 | — |
case-15 | pass→pass | 10,167 | 5,640 | -45% | 1 | 1 | 0% | 1,758 | 2,456 | +40% | 0 | 0 | — |
case-16 | fail→pass | 14,762 | 7,326 | -50% | 1 | 1 | 0% | 2,402 | 2,754 | +15% | 0 | 0 | — |
case-17 | pass→pass | 15,831 | 11,140 | -30% | 1 | 1 | 0% | 2,674 | 3,203 | +20% | 0 | 0 | — |
case-18 | pass→pass | 12,813 | 8,802 | -31% | 1 | 1 | 0% | 2,201 | 2,981 | +35% | 0 | 0 | — |
case-19 | pass→pass | 13,075 | 7,950 | -39% | 1 | 1 | 0% | 2,119 | 2,840 | +34% | 0 | 0 | — |
case-20 | fail→pass | 13,191 | 9,218 | -30% | 1 | 1 | 0% | 1,978 | 3,045 | +54% | 0 | 0 | — |
case-21 | pass→pass | 13,947 | 8,519 | -39% | 1 | 1 | 0% | 2,128 | 2,772 | +30% | 0 | 0 | — |
case-22 | pass→pass | 6,823 | 6,342 | -7% | 1 | 1 | 0% | 1,117 | 2,521 | +126% | 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 +27 percentage points is the difference between those two pass rates over the 22 comparable cases. 3 cases got worse with the skill loaded, and they are 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.