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 skills/pair-systems-inc/goodmem-claude-code-plugin/pythonnpx skills add PAIR-Systems-Inc/goodmem-claude-code-plugin --skill pythongit clone --depth 1 https://github.com/PAIR-Systems-Inc/goodmem-claude-code-pluginWhat 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 | $0.00049 | $0.00350 |
| Opus 5 | $0.00024 | $0.00175 |
| Sonnet 5 | $0.00010 | $0.00070 |
| Haiku 4.5 | $0.00005 | $0.00035 |
Grade A, and why
goodmem:python 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 2d 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 Python SDK. Use it to write Python code that accomplishes the user's request.
See reference.md for the complete API reference including all method signatures, convenience shortcuts, available model identifiers, error handling, and common patterns.
Key principles:
- Context managers recommended:
with Goodmem(...) as client:(plain construction is fine in short scripts) - For create methods, pass flat kwargs (convenience transforms handle the rest)
- For update methods, pass either a typed request object or a plain dict
- Use
model_identifierfor embedders/LLMs/rerankers — the SDK auto-infers provider, endpoint, etc. - Use
api_key="sk-..."on create (notcredentials) — the SDK builds the credential struct - Iterate paginated results directly:
for item in client.spaces.list(): - Use
stream=Falseon retrieve if you want a plain list instead of a stream - SaaS endpoints require
api_key: creating an embedder/LLM/reranker for a known SaaS provider (OpenAI, Cohere, Voyage, Jina, Anthropic, Google, Mistral) withoutapi_keyraisesValueError: Provider '...' at '...' requires an API key.— always passapi_key="sk-..."
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.
- 2d ago First seen · 21 lines · 49 tokens per session scan A 0debad599cb6
goodmem:python is a skill published in the GitHub repository PAIR-Systems-Inc/goodmem-claude-code-plugin (8 stars, last pushed 3d ago), licensed MIT. It adds 49 tokens to every session and 350 once invoked, about $0.0002 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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