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 PAIR-Systems-Inc/goodmem-claude-code-plugin --skill javagit clone --depth 1 https://github.com/PAIR-Systems-Inc/goodmem-claude-code-pluginWrote 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/pair-systems-inc/goodmem-claude-code-plugin/java)<a href="https://agentmods.dev/skills/pair-systems-inc/goodmem-claude-code-plugin/java"><img src="https://agentmods.dev/badge/skills/pair-systems-inc/goodmem-claude-code-plugin/java/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/pair-systems-inc/goodmem-claude-code-plugin/java"><img src="https://agentmods.dev/badge/skills/pair-systems-inc/goodmem-claude-code-plugin/java.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00045 | $0.00410 |
| Opus 5.5 | $0.00018 | $0.00164 |
| Sonnet 5.5 | $0.00009 | $0.00082 |
| Haiku 4.5 | $0.00005 | $0.00041 |
Grade A, and why
goodmem:java 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 1mo 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.
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
You have access to the GoodMem Java SDK. Use it to write Java code that accomplishes the user's request.
See reference.md for install instructions, common request builders, streaming, pagination, async usage, typed IDs, and end-to-end snippets.
Key principles:
- Use
Goodmem.builder().baseUrl(...).apiKey(...).build()and prefer try-with-resources. - Use
AsyncGoodmemwhen the user asks for async code; async methods returnCompletableFuture<T>. - Import request/response records from
ai.pairsys.goodmem.client.models. - Use request builders for creates and updates, for example
EmbedderCreationRequest.builder()...build(). - For SaaS providers, pass the provider API key to create calls, for example
client.embedders.create(request, openaiApiKey). - Use
modelIdentifier(...)for embedders, LLMs, and rerankers; the SDK auto-infers provider details. - Preserve typed handles such as
SpaceId,MemoryId,EmbedderId,LlmId, andRerankerId. - Create spaces with
List.of(new SpaceEmbedderConfig(embedderId, null)). - Iterate paginated results directly with
Page<T>orAsyncPage<T>; list optionmaxResultstakes an integer page size. - Use try-with-resources for streaming types such as
RetrieveMemoryStreamandPingStream. - Use the file-upload convenience
client.memories.create(spaceId, Path.of(...))instead of manual base64 encoding. - Compare typed enums directly, for example
status == MemoryProcessingStatus.COMPLETED.
What ships with it
1 file 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.
- 1mo ago First seen · 25 lines · 45 tokens per session scan A 5eb8deccb48b
goodmem:java is a skill published in the GitHub repository PAIR-Systems-Inc/goodmem-claude-code-plugin (9 stars, last pushed 4d ago), licensed MIT. It adds 45 tokens to every session and 410 once invoked, about $0.0002 per session on Opus 5.5. 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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Ask any natural language question about the memory graph. You generate Cypher directly and execute it. Use when the user has a complex or ad-hoc question that the standard graph tools don't cover.
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Transcribe a local audio or video file using Whisper and ingest it into the memory graph. Use when the user has a local MP3, WAV, M4A, MP4, or similar audio/video file they want to add to their knowledge graph.
ingest
Ingest a file or URL into the memory graph. Handles local files (text, PDF, DOCX, XLSX, images, etc.) and URLs (web pages, YouTube, Wikipedia, RSS). Use when the user wants to add any document or web content to their knowledge graph.