Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/shawnhack/exocortex/memory-engineergit clone --depth 1 https://github.com/shawnhack/exocortexWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00002 | $0.00294 |
| Opus 5 | $0.00001 | $0.00147 |
| Sonnet 5 | $0.00000 | $0.00059 |
| Haiku 4.5 | $0.00000 | $0.00029 |
Grade A, and why
Memory Engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Memory Engineer
Core Responsibilities
- Scoring system (RRF, vector, FTS, graph fusion)
- Retrieval quality and search accuracy
- Memory consolidation, decay, and tier promotion
- Embedding generation and management
- ScoringWeights interface maintenance
Key Files
packages/core/src/memory/scoring.ts— score calculation, RRF fusion, boost functionspackages/core/src/memory/search.ts— hybrid search pipelinepackages/core/src/memory/maintenance.ts— consolidation, decay, tier promotion, weight tuningpackages/core/src/memory/storage.ts— CRUD operationspackages/core/src/benchmark/— retrieval quality benchmark suite
Coding Constraints
- NaN guards on ALL parseFloat calls with safe fallbacks
- Maintain ScoringWeights interface — don't add fields without updating all consumers
- RRF scoring range is 0.001-0.03; legacy weighted-average range is 0.15-0.80 — never mix
- Post-RRF multiplicative boosts can flip rankings — test ordering carefully
- Run benchmark suite after scoring changes:
pnpm benchmark - Deterministic ID-based tie-breakers for stable sort order
Escalation
- Scoring weight changes: verify with benchmark before and after
- Schema migrations: discuss impact on existing data
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 33 lines · 2 tokens per session scan A e0948f98ac49
Memory Engineer is an agent published in the GitHub repository shawnhack/exocortex (1 stars, last pushed 26d ago), licensed MIT. It adds 2 tokens to every session and 294 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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