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A5c AI/Vector Memory — measured AI agent skill | DecimalAI

a5c-ai/vector-memory

SkillScore48Maintained

HNSW vector search for pattern similarity retrieval and knowledge graph maintenance with PageRank scoring, community detection, and 3-tier memory management.

by a5c-ai

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

AI Engineer pack

decimalai skills pull a5c-ai-vector-memory

Get this skill — curl · raw file

curl -fsSL https://app.decimal.ai/s/a5c-ai-vector-memory/SKILL.md

Raw file: /s/a5c-ai-vector-memory/SKILL.md ↗ · machine-readable summary at /s/a5c-ai-vector-memory.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

23 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 9d ago

—-34% tokens0% turns48% of whole cases pass with skill (11/23)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-03	✗→✓	▲ Improved	40%	0%
case-04	✗→✓	▲ Improved	-62%	0%
case-05	✗→✓	▲ Improved	-78%	0%
case-06	✗→✓	▲ Improved	-66%	0%
case-07	✗→✓	▲ Improved	-15%	0%

Showing 5 of 23 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 7/31/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

a5c-ai / babysitter

library/methodologies/ruflo/skills/vector-memory/SKILL.md

View on GitHub ↗

License MITImported 7/31/2026Version v1

Skill contents

SKILL.md

Building and querying knowledge graphs for project context
Managing cross-session memory across project/local/user scopes
Fast similarity search for routing decisions

HNSW Performance

Search latency: ~61 microseconds
Query throughput: ~16,400 QPS
Configurable embedding dimensions (default: 128)

Knowledge Graph

PageRank: Importance scoring for knowledge nodes
Community Detection: Cluster related patterns
LRU Cache: Fast access to frequently used patterns
SQLite Backing: Persistent cross-session storage

3-Tier Memory

| Scope | Persistence | Content | |-------|------------|---------| | Project | Codebase-level | Patterns, architecture decisions, dependencies | | Local | Session-level | Context, adaptations, temporary patterns | | User | Cross-project | Preferences, learned behaviors, global patterns |

Agents Used

agents/optimizer/ - Memory and cache optimization

Tool Use

Invoke via babysitter process: methodologies/ruflo/ruflo-intelligence

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Other measured skills in the registry, with their headline benchmark lift.