Skip to content
ai-supply.store
탐색카테고리리더보드커뮤니티Agent APIFAQ
로그인무료 가입
catalog / Language & NLP / LLM Prompt Library
❝PromptLanguage & NLPFree

LLM Prompt Library

Experimental prompts, Jinja2 templates, and scripts spanning OpenAI, Anthropic, Google, Mistral and more.

@ai-supply
설치 수32k
⟳ upstream v1.1.0 · updated 1y ago
↗ 소스 저장소
← More Language & NLPLanguage & NLP leaderboard →How we grade security →Source ↗
✓ Grade A · 100/100 · SafeSecurity assessment
✓No compromise signals1capabilities surfaced11of 20 OWASP controls clear
Prompt-injection phrasing · expected
scanned 1mo ago·osv · gitleaks · opengrep · picklescan + heuristics·full breakdown in the Security tab ↓

LLM Prompt Library

An experimental library of prompts, Jinja2 templates, and helper scripts spanning many model families (OpenAI, Anthropic, DeepSeek, Meta, Mistral, Google, xAI and others).

It covers a wide range of tasks — writing, analysis, coding, math, and structured extraction — with templated prompts you can parameterize and reuse programmatically.

MIT licensed; a practical starting point for building your own reusable, provider-agnostic prompt toolkit.

Rating rank
#1
of 30 in Language & NLP
Install rank
#19
of 30 in Language & NLP
Security score
100/100 · A
safe
Security rank
#1
of 30 in Language & NLP
Installs
32k
cat avg 145k
This listing vs category average
Installs
this
cat avg
Security (of 100)
this
cat avg
Adoption trend
See the Language & NLP leaderboard →
✓ Security: Safe · 100100/100 · grade Ascanned 1mo ago
✓ no compromise signals1 risk-surface · 2/20 OWASP controls flagged

Compromise signals — malicious or tampered code (leaked secrets, backdoors, a dropped executable) — reduce the score, and known dependency CVEs carry a bounded penalty (they warrant review but never QUARANTINE — update the dependency to clear). Other dangerous-by-capability traits are risk surface, expected for some capabilities. Every finding is mapped to its OWASP control below.

Prompt card · med confidence (static)
{placeholders}{variables}{scene}{prompt}{scenario}{contract}{brief}{post}{trial}{question}{symptoms}{phase}{insert}{details}{name}injection surface present⚠ jailbreak taxonomy present

Findings mapped to the OWASP Top 10 for LLM Applications (2025) and the OWASP Machine Learning Security Top 10. Expand any flagged control for the exact findings — compromise reduces the score; expected/risk-surface do not, except a known CVE, which carries a small bounded penalty (high/critical → Review).

OWASP Top 10 for LLM Applications
⚠LLM01Prompt Injectionhigh
Adversarial instructions embedded in an artifact that hijack a downstream LLM.
•Prompt-injection phrasing — instruction-subversion language detected · abilzerian-LLM-Prompt-Library-bd95570/prompts/miscellaneous/ChatAGI.md (CWE-77)expected
§LLM09MisinformationGovernance
Artifacts designed to produce false/deceptive output.
Detectable only by runtime behavioral evaluation; addressed via responsible-use attestation.
◷LLM10Unbounded ConsumptionRuntime-enforced
Unbounded loops/recursion causing DoS or runaway cost.
Enforced at runtime by the gateway (rate limits + spend caps + size caps); static check flags unbounded loops.
✓LLM02Sensitive Information DisclosurePassed
✓LLM03Supply ChainPassed
✓LLM04Data and Model PoisoningPassed
Backdoors/poisoning in training data or serialized models.
Behavioral poisoning needs model execution; static check covers unsafe serialization + dataset skew only.
✓LLM05Improper Output HandlingPassed
✓LLM06Excessive AgencyPassed
✓LLM07System Prompt LeakagePassed
✓LLM08Vector and Embedding WeaknessesPassed
PII or plaintext source leakage in embedding/vector exports.
Embedding inversion/poisoning is largely runtime; static check covers PII in vector exports.
OWASP Machine Learning Security Top 10
⚠ML02Data Poisoninghigh
Poisoned training datasets with triggers or anomalous distributions.
Static check covers trigger phrasing, PII and label skew; full poisoning detection is runtime.
•Prompt-injection phrasing — instruction-subversion language detected · abilzerian-LLM-Prompt-Library-bd95570/prompts/miscellaneous/ChatAGI.md (CWE-77)expected
§ML01Input Manipulation (Adversarial)Governance
Models vulnerable to adversarial perturbations.
Requires runtime robustness evaluation; addressed via publisher robustness attestation.
§ML03Model InversionGovernance
Training data reconstructable from a model's outputs.
Runtime/evaluation property; addressed via model-card data-provenance + DP attestation.
§ML04Membership InferenceGovernance
Determining whether a record was in the training set.
Runtime/evaluation property; addressed via overfitting disclosure + DP attestation.
§ML08Model SkewingGovernance
Models trained on skewed data producing biased output.
Requires fairness evaluation; addressed via model-card bias/limitations disclosure.
◷ML09Output IntegrityRuntime-enforced
Middleware tampering with model outputs in transit.
Gateway enforces TLS + response integrity; static check flags output-rewriting code.
✓ML05Model TheftPassed
Unlicensed re-distribution / license-incompatible derivatives.
Static check verifies license declaration; extraction throttling is runtime.
✓ML06AI Supply ChainPassed
✓ML07Transfer Learning AttackPassed
Backdoored base models / LoRA adapters propagating to derivatives.
Backdoor detection needs behavioral probing; static check covers unsafe serialization + provenance.
✓ML10Model Poisoning (Weights)Passed
Tampered model weight files; integrity must be verifiable.
Static check enforces safe formats + records a content hash for downstream verification.
Other findings (5) · hygiene / uncategorized
•Unrecognized file type — '.gitattributes' is not on the allowlist · abilzerian-LLM-Prompt-Library-bd95570/.gitattributesrisk surface
•Unrecognized file type — '.gitignore' is not on the allowlist · abilzerian-LLM-Prompt-Library-bd95570/.gitignorerisk surface
•Unrecognized file type — '.cff' is not on the allowlist · abilzerian-LLM-Prompt-Library-bd95570/CITATION.cffrisk surface
•Unrecognized file type — '.?' is not on the allowlist · abilzerian-LLM-Prompt-Library-bd95570/LICENSErisk surface
•Unrecognized file type — '.j2' is not on the allowlist · abilzerian-LLM-Prompt-Library-bd95570/templates/ai_research/ai_ablation_spec_generator_v1.j2risk surface
✔ verified source · pinned abilzerian-LLM-Prompt-Library-bd95570
Check against a policy

The same gate an agent runs before installing (POST /api/v1/trust/llm-prompt-library/check). Click a policy:

Consume LLM Prompt Library programmatically. Authenticate with an API key or session — see Authorize an agent.

# Agents: CHECK BEFORE YOU INSTALL (no auth) — score, grade, level, capability manifest
curl https://ai-supply.store/api/v1/trust/llm-prompt-library

# Gate against your org policy (returns { pass, violations })
curl -X POST https://ai-supply.store/api/v1/trust/llm-prompt-library/check \
  -H "Content-Type: application/json" \
  -d '{"minGrade":"B","denyPermissions":["shell"],"denyUnknownEgress":true}'

# CLI
npx ai-supply add llm-prompt-library

# REST (install → download)
curl -X POST https://ai-supply.store/api/v1/listings/llm-prompt-library/install \
  -H "Authorization: Bearer $AIM_KEY"

# MCP tool
install_listing({ "slug": "llm-prompt-library" })
OpenAPI spec →
vlatest
✓ Security: Safe · 1001mo ago

Curated mirror — latest upstream source. See the repository for tagged releases.

Sign in and install this listing to leave a review.

More from @ai-supply

View profile →
◉Agent
MetaGPT
Multi-agent framework that assigns GPT roles (PM, engineer, QA) to solve complex software tasks end-to-end.
↓ 1.0M
⇄Connector
vLLM
High-throughput, memory-efficient LLM inference engine with PagedAttention and continuous batching.
↓ 892k
⇄Connector
Meilisearch
Lightning-fast open-source search engine with typo-tolerance, semantic hybrid search, and sub-50ms response times.
↓ 811k
△Eval
Weights & Biases (wandb)
ML experiment tracking and visualization — log metrics, hyperparameters, models, and media in real time.
↓ 784k
ai-supply.store

무료로 제공하는 보안 검증 AI 역량 — skill, MCP, plugin, agent, 데이터셋을 비롯한 모든 항목에 보안 점수를 매기고 최신성을 추적하며, 사람과 agent 모두를 위해 만들었습니다.

api · v3.1status · all green
문의하기
support@ai-supply.storesecurity@ai-supply.store
카탈로그
  • 탐색
  • 카테고리
  • 리더보드
  • 벤치마크
  • 보안
  • Scan a repo
커뮤니티
  • 커뮤니티
  • FAQ
에이전트용
  • 빠른 시작 (60s)
  • 에이전트 승인
  • Agent API
  • OpenAPI 사양
빌더용
  • 게시
  • 대시보드
계정
  • 계정 만들기
  • 로그인
  • 설정
법적 정보
  • 이용약관
  • 게시자 계약
  • 이용 정책
  • 개인정보 처리방침