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 skills add aiappsgbb/awesome-gbb --skill foundry-memorygit clone --depth 1 https://github.com/aiappsgbb/awesome-gbbWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aiappsgbb/awesome-gbb/foundry-memory)<a href="https://agentmods.dev/skills/aiappsgbb/awesome-gbb/foundry-memory"><img src="https://agentmods.dev/badge/skills/aiappsgbb/awesome-gbb/foundry-memory.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
- medium Data Exfiltration · line 146 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
What 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 5.1 | $0.00150 | $0.05064 |
| Opus 5 | $0.00075 | $0.02532 |
| Sonnet 5 | $0.00030 | $0.01013 |
| Haiku 4.5 | $0.00015 | $0.00506 |
Grade A, and why
foundry-memory scanned grade A with 1 finding 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 7d ago.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST \ How it starts
The opening of the file, as written. The whole thing — 634 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Foundry Memory
Foundry Memory Store is the native Azure AI Foundry feature for persistent agent memory across sessions. It gives a Foundry agent a managed long-term memory layer instead of requiring an external sidecar such as Mem0.
It stores three memory types:
- User profiles — durable facts and preferences about a user (for example, preferred units, UI settings, loyalty program, or role context).
- Chat summaries — distilled cross-session summaries of prior threads so a later conversation can resume without replaying the full transcript.
- Procedural memory — codified procedures the agent has learned through
experience (for example, "when the user asks for a refund, always confirm
the order ID first"). Procedural memory is opt-in per store via
procedural_memory_enabled=True.
Use it when the memory is user-scoped, conversational, and agent-native.
If the problem is document grounding or enterprise RAG over files, use
foundry-iq instead.
1. Overview
Foundry Memory is a managed long-term memory subsystem inside Foundry Agent Service. The service extracts salient facts from conversations, consolidates duplicates, and makes the results searchable for later turns or later sessions.
Key platform facts:
- SDK floor:
azure-ai-projects>=2.0.0 - Python entry point:
project_client.beta.memory_stores - REST API version:
2025-11-15-preview - Native replacement for older Mem0 patterns: prefer Foundry Memory when the workload already lives in Foundry Agent Service
- Agent integration: attach the
memory_search_previewtool so the agent can read and write memory automatically during conversations
2. Prerequisites
Before you create a memory store, make sure the project has:
- A Foundry project endpoint such as
https://<project>.services.ai.azure.com/api/projects/<project-name> - A compatible chat model deployment for extraction / consolidation
- A compatible embedding model deployment for semantic retrieval
azure-ai-projects>=2.0.0plusazure-identityfor Python- Preview API access for
2025-11-15-preview
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 634 lines · 150 tokens per session scan A 1fae44f3d2b0
foundry-memory is a skill published in the GitHub repository aiappsgbb/awesome-gbb (5 stars, last pushed yesterday), licensed MIT. It adds 150 tokens to every session and 5,064 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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