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-demand_forecaster)<a href="https://agentmods.dev/agents/sandeeprdy1729/timps-swarm/timps-demand_forecaster"><img src="https://agentmods.dev/badge/agents/sandeeprdy1729/timps-swarm/timps-demand_forecaster/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-demand_forecaster"><img src="https://agentmods.dev/badge/agents/sandeeprdy1729/timps-swarm/timps-demand_forecaster.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 | $0.00067 | $0.00509 |
| Opus 5 | $0.00034 | $0.00254 |
| Sonnet 5 | $0.00013 | $0.00102 |
| Haiku 4.5 | $0.00007 | $0.00051 |
Grade A, and why
timps_demand_forecaster 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 8d 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.
This is a copy
88% identical to timps_db_agent — 16 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
demand forecaster
You are the demand forecaster sub-agent from the TIMPS Swarm (category: priority).
Your job
Produce a SKU/location-level demand forecast with seasonality, promotions, and trend. Returns intervals, backtest MAPE/MASE, and an ordering recommendation.
How to respond
- Always call the MCP tool
timps_demand_forecasterexactly once via themcp__timps-swarm__timps_demand_forecastertool 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_demand_forecaster 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.
- 8d ago First seen · 45 lines · 67 tokens per session scan A 1af1e3e3d8a7
timps_demand_forecaster is an agent published in the GitHub repository Sandeeprdy1729/timps-swarm (1 stars, last pushed 6d ago), licensed MIT. It adds 67 tokens to every session and 509 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to timps_db_agent, differing in 16 lines, and is treated as a copy.
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.
researcher
Run deep research with grounded references, systematic exploration, self-validation, etc. Full subagent.
God Agent Metis — Project Manager & Execution Planner
God Agent Metis — Project Management & Execution Planning. Titaness of wisdom, cunning, and practical intelligence — the first wife of Zeus, and the.
thoughts-analyzer
The research equivalent of codebase-analyzer. Use this subagenttype when wanting to deep dive on a research topic. Not commonly needed otherwise.
Demonstrate
Agent for demonstrating VS Code features.