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Get Started Free →Verifies a package exists before install, defending against hallucination and slopsquatting. Use when adding, recommending, or installing a package.
.claude/skills/athola-dependency-verification/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-14 | ✗→✓ | ▲ Improved | 46% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 17% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -3% | 0% |
| case-12 | ✗→✓ | ▲ Improved | -27% | 0% |
| case-13 | ✗→✓ | ▲ Improved | -28% | 0% |
> A package name the model produced is a claim, not a fact. The > registry is the fact. Verify before you install.
Code-generating language models recommend packages that do not exist at a measured rate of 5.2% (commercial models) to 21.7% (open models) across 576,000 samples (Spracklen et al. 2024, arXiv 2406.10279). Worse, 58% of hallucinated names recur across reruns, so an attacker can predict them, register the empty name, and ship malware. This is "slopsquatting." A proof-of-concept package (huggingface-cli) drew over 30,000 downloads after being registered against a commonly hallucinated name. Package hallucination is also inversely correlated with coding-benchmark score, so a better model does not make this go away.
The defense is cheap: confirm the name exists in its registry before installing or recommending it. This skill defines that check and is enforced by the guard_package_hallucination.py PreToolUse hook.
Apply before any of these:
pip install, uv add, npm install, pnpm add,yarn add, cargo add, poetry add, or pdm add.
pyproject.toml, requirements.txt,package.json, or Cargo.toml.
sanctum:version-updates)
leyline:supply-chain-advisory)
A package fails verification on either signal:
a likely hallucination. Do not install it. Search for the correct name or confirm the package was renamed or removed.
popular package (for example reqeusts versus requests). This is either a typo or a deliberate impersonation. Confirm the exact name you intend before proceeding.
A name that is unknown to the bundled popular-package set but present in the registry passes. A name that cannot be checked because the registry is unreachable is reported as unverified, never blocked: the guard does not fail closed on a network error.
Registry existence is the pass/fail check. Real-world usage is a separate, softer signal that builds confidence on top of it. Once a package clears the two signals above, cross-checking that it is actually used by other projects raises your confidence that the name is the established one rather than a freshly-registered impostor that happens to exist.
Useful confidence signals, none of them blocking:
(an established package is imported across many repositories).
the package's source.
name registered yesterday is a red flag; a modest name with years of releases is reassuring).
Treat low usage as a prompt to look closer, never as a reason to reject on its own. New, niche, internal, and private packages are legitimately low-usage, so a missing GitHub footprint must not block an install the registry already confirmed. Use this signal to build confidence and to disambiguate between two similarly-named packages, not to gate.
would fetch (strip version specifiers and flags).
registry-checks.md for the per-ecosystem endpoints and the offline-degradation rule.
name and confirm it is the one you meant.
HTTP status) when the install lands in a PR, per imbue:proof-of-work.
The guard_package_hallucination.py hook runs this check automatically on every Bash install command. Shadow mode (warn only) is the default; set VOW_SHADOW_MODE=0 to block typosquat and nonexistent installs. Disable the network lookup with IMBUE_PKG_REGISTRY_CHECK=0 to rely on the offline typosquat signal alone. The hook is a backstop, not a substitute: verify deliberately when you add a dependency rather than waiting for the gate.
imbue:proof-of-work: capture the registry check as evidence.leyline:supply-chain-advisory: broader dependency supply-chainauditing (lockfile drift, artifact integrity, bad versions).
confirmed present in its registry, or the install is abandoned.
and confirmed before install.
unverified and not silently installed.
proof-of-work evidence.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-08 | pass→pass | 13,397 | 13,453 | +0% | 1 | 1 | 0% | 2,219 | 3,400 | +53% | 0 | 0 | — |
case-14 | fail→pass | 9,716 | 6,206 | -36% | 1 | 1 | 0% | 1,683 | 2,461 | +46% | 0 | 0 | — |
case-07 | pass→pass | 18,087 | 8,769 | -52% | 1 | 1 | 0% | 3,007 | 2,739 | -9% | 0 | 0 | — |
case-01 | fail→fail | 6,574 | 6,218 | -5% | 1 | 1 | 0% | 398 | 1,582 | +297% | 0 | 0 | — |
case-02 | pass→pass | 8,181 | 4,578 | -44% | 1 | 1 | 0% | 1,396 | 1,992 | +43% | 0 | 0 | — |
case-03 | pass→pass | 13,393 | 4,785 | -64% | 1 | 1 | 0% | 2,078 | 1,999 | -4% | 0 | 0 | — |
case-04 | fail→pass | 11,064 | 4,947 | -55% | 1 | 1 | 0% | 1,746 | 2,050 | +17% | 0 | 0 | — |
case-05 | fail→pass | 13,115 | 4,816 | -63% | 1 | 1 | 0% | 2,170 | 2,103 | -3% | 0 | 0 | — |
case-06 | pass→fail | 14,341 | 6,390 | -55% | 1 | 1 | 0% | 2,342 | 2,317 | -1% | 0 | 0 | — |
case-09 | pass→pass | 12,353 | 6,204 | -50% | 1 | 1 | 0% | 2,011 | 2,346 | +17% | 0 | 0 | — |
case-10 | pass→pass | 9,217 | 5,748 | -38% | 1 | 1 | 0% | 1,478 | 2,305 | +56% | 0 | 0 | — |
case-11 | pass→pass | 11,577 | 6,285 | -46% | 1 | 1 | 0% | 1,928 | 2,328 | +21% | 0 | 0 | — |
case-12 | fail→pass | 14,488 | 2,371 | -84% | 1 | 1 | 0% | 2,350 | 1,710 | -27% | 0 | 0 | — |
case-13 | fail→pass | 12,891 | 1,686 | -87% | 1 | 1 | 0% | 2,162 | 1,563 | -28% | 0 | 0 | — |
case-15 | pass→pass | 11,531 | 6,848 | -41% | 1 | 1 | 0% | 1,976 | 2,514 | +27% | 0 | 0 | — |
case-16 | pass→pass | 8,880 | 4,621 | -48% | 1 | 1 | 0% | 1,461 | 2,065 | +41% | 0 | 0 | — |
case-17 | pass→pass | 14,200 | 6,697 | -53% | 1 | 1 | 0% | 2,305 | 2,504 | +9% | 0 | 0 | — |
case-18 | pass→pass | 12,197 | 5,486 | -55% | 1 | 1 | 0% | 1,969 | 2,272 | +15% | 0 | 0 | — |
case-19 | pass→pass | 11,544 | 2,152 | -81% | 1 | 1 | 0% | 1,869 | 1,619 | -13% | 0 | 0 | — |
case-20 | fail→pass | 11,664 | 4,784 | -59% | 1 | 1 | 0% | 1,676 | 2,117 | +26% | 0 | 0 | — |
case-21 | pass→pass | 2,860 | 2,111 | -26% | 1 | 1 | 0% | 563 | 1,642 | +192% | 0 | 0 | — |
case-22 | fail→pass | 7,961 | 4,907 | -38% | 1 | 1 | 0% | 1,373 | 2,127 | +55% | 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, and 21 counted toward the lift figure. The other 1 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +27 percentage points is the difference between those two pass rates over the 21 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.