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.
git 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-content_multiplier)<a href="https://agentmods.dev/agents/sandeeprdy1729/timps-swarm/timps-content_multiplier"><img src="https://agentmods.dev/badge/agents/sandeeprdy1729/timps-swarm/timps-content_multiplier/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/agents/sandeeprdy1729/timps-swarm/timps-content_multiplier"><img src="https://agentmods.dev/badge/agents/sandeeprdy1729/timps-swarm/timps-content_multiplier.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 | $0.00063 | $0.00494 |
| Opus 5 | $0.00032 | $0.00247 |
| Sonnet 5 | $0.00013 | $0.00099 |
| Haiku 4.5 | $0.00006 | $0.00049 |
Grade A, and why
timps_content_multiplier 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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- timps_quantum_ready — 86% identical, 20 lines differ
What it actually says
content multiplier
You are the content multiplier sub-agent from the TIMPS Swarm (category: developer).
Your job
Transform a long-form technical post into multiple short-form formats: tweet thread, LinkedIn post, changelog entry, docs blurb, and HN title.
How to respond
- Always call the MCP tool
timps_content_multiplierexactly once via themcp__timps-swarm__timps_content_multipliertool 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_content_multiplier 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.
- 6d ago Changed · -4 lines 17ea14f43530
- 9d ago First seen · 49 lines · 63 tokens per session scan A e64f160f9227
timps_content_multiplier is an agent published in the GitHub repository Sandeeprdy1729/timps-swarm (1 stars, last pushed 7d ago), licensed MIT. It adds 63 tokens to every session and 494 once invoked, about $0.0003 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.
Other agents, from other repositories
test-case-result-validator
Compares old vs new instruction outputs against original codebase, scores 8 quality categories, emits pass/fail JSON verdict for CI/CD validation pipeline.
requirements-engineer
Author, refine, and finalize requirements and specifications with traceability. Full subagent.
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.
God Agent Calliope — Email Design Agent
God Agent Calliope — Email Design & HTML/MJML. Muse of epic poetry and eloquence. Calliope gives precise, beautiful words their perfect f.
Logos — UX Research & Systems Agent
God Agent — UX Research Synthesizer & Systems Thinker. Logos (λόγος) — the Stoic concept of reason, order, and the rational principle that govern.
thoughts-analyzer
The research equivalent of codebase-analyzer. Use this subagenttype when wanting to deep dive on a research topic. Not commonly needed otherwise.