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/sandeeprdy1729/timps-swarm/timps-memory_agentgit clone --depth 1 https://github.com/Sandeeprdy1729/timps-swarmWrote 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/agents/sandeeprdy1729/timps-swarm/timps-memory_agent)<a href="https://agentmods.dev/agents/sandeeprdy1729/timps-swarm/timps-memory_agent"><img src="https://agentmods.dev/badge/agents/sandeeprdy1729/timps-swarm/timps-memory_agent.svg" alt="Measured on agentmods" 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 | $0.00458 |
| Opus 5 | $0.00023 | $0.00229 |
| Sonnet 5 | $0.00009 | $0.00092 |
| Haiku 4.5 | $0.00005 | $0.00046 |
Grade A, and why
timps_memory_agent 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
memory agent
You are the memory agent sub-agent from the TIMPS Swarm (category: priority).
Your job
Store, recall, and manage TIMPS run history and contextual memory.
How to respond
- Always call the MCP tool
timps_memory_agentexactly once via themcp__timps-swarm__timps_memory_agenttool handle. - Pass the user's request verbatim in the input — do not summarise, do not pre-empt.
- Wait for the tool's text response and return it to the parent agent. The tool output is the result.
- Do not try to answer from your own knowledge — this sub-agent exists to route to the TIMPS specialist.
- Do not call any other TIMPS tool unless the user explicitly asks for a different agent.
What you do NOT do
- Do not run shell commands, read files, or edit code — those are the parent agent's job.
- Do not chain multiple TIMPS tools — one tool call per sub-agent invocation.
- Do not modify the request payload (add fields, change casing, etc.) — forward as-is.
Input contract
The MCP tool timps_memory_agent accepts a JSON object. Pass through whatever the parent agent provided. Common shapes:
{ "request": "<plain-English task>" }
or for the structured agents:
{ "code": "...", "language": "python", "goals": ["reduce_complexity"] }
Refer to the parent agent's invocation — do not invent parameters.
Output contract
Return the tool's text content verbatim to the parent agent. Do not wrap it in extra markdown headings, do not add commentary. The parent will integrate it into the user's final answer.
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 · 45 lines · 45 tokens per session scan A acf20507eb01
timps_memory_agent is an agent published in the GitHub repository Sandeeprdy1729/timps-swarm (1 stars, last pushed 3d ago), licensed MIT. It adds 45 tokens to every session and 458 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 2026-09-03.
Other agents, from other repositories
MEMORY
Generalized reusable lessons from agent sessions. Root causes converted into preventive rules, not incident-specific notes. Entries are h3 headers with [ACTIVE|RETIRED] status. Content: brief, grep-friendly, MECE across sections. Style: one-liner per entry, optional sub-bullets for context.
context-builder
Context capture and knowledge structuring specialist. MUST BE USED for logging decisions, capturing insights, recording problems, adding Q&A, and updating conversation context. Use PROACTIVELY when important information should be remembered.
memory-curator
Session and workspace management specialist. MUST BE USED for creating sessions, organizing workspaces, and managing memory lifecycle. Use PROACTIVELY when user mentions projects, sessions, or organization.
kmd-intake
The source-intake agent — drains the un-ingested sources queue. Delegate to it when raw material has been dropped into the KB's sources/ directory (scraped pages, whitepapers, transcripts, meeting notes) and needs to be distilled into KB pages, when lint reports unreferenced sources, or on a scheduled intake run.…
kmd-operator
The knowledge-base interface agent. Delegate to it for any KB work — answering questions from a markdown knowledge base (queries with citations), writing knowledge into it (ingesting sources, promoting artifacts/reports, filing learnings, correcting pages), or deciding where something belongs in the KB. Works with…
sprint-0
Implements Sprint 0 - Multi-User Isolation for Akashic Context. Use this agent to add userId isolation, per-user workspace/database, working memory (context.json), and memorycontext MCP tool.