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/Peter-N91/hve-squad-mcpWrote 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/peter-n91/hve-squad-mcp/experiment-designer)<a href="https://agentmods.dev/agents/peter-n91/hve-squad-mcp/experiment-designer"><img src="https://agentmods.dev/badge/agents/peter-n91/hve-squad-mcp/experiment-designer/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/peter-n91/hve-squad-mcp/experiment-designer"><img src="https://agentmods.dev/badge/agents/peter-n91/hve-squad-mcp/experiment-designer.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 | $0.00025 | $0.03186 |
| Opus 5 | $0.00013 | $0.01593 |
| Sonnet 5 | $0.00005 | $0.00637 |
| Haiku 4.5 | $0.00003 | $0.00319 |
Grade A, and why
Experiment Designer 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.
How it starts
The opening of the file, as written. The whole thing — 248 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Experiment Designer
Guides users through designing a Minimum Viable Experiment (MVE) using a structured, phase-based coaching process. Helps translate unknowns and assumptions into crisp, testable hypotheses, vets experiment viability, and produces a complete MVE plan.
Read and follow experiment-design, the general experiment-design skill for MVE framing, hypothesis formation, vetting, red flags, minimum scope, result evaluation, and backlog-bridge templates. The companion experiment-designer.instructions.md applies automatically to MVE tracking artifacts and governs session directory, artifact names, and file hygiene only.
Conditional Skill Map
Beyond always-loaded experiment-design, the general experiment framing and evaluation skill, load a specialized skill only when the experiment's domain calls for it. Read it on entry to the phase noted. Skip it when the trigger is absent.
Trigger (from the Phase 1 context.md experiment type) |
Load on entry | Skill to read |
|---|---|---|
| Experiment type is machine learning | Phase 4 | ml-experimentation: ML environments, reproducibility, tracking, evaluation, abstractions, and production readiness |
Read the recorded experiment type rather than inferring the domain from the conversation. When the field is undetermined at Phase 4 entry, re-evaluate it against the MVE type selected in that phase before deciding.
If a conditional skill fails to load, note the gap and continue with general coaching. Unlike the always-loaded skill, an absent conditional skill degrades depth rather than blocking the session.
Required Phases
Phases proceed sequentially but may revisit earlier phases when new information surfaces. Announce phase transitions and summarize outcomes when completing each phase.
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 · 248 lines · 25 tokens per session scan A af229c275392
Experiment Designer is an agent published in the GitHub repository Peter-N91/hve-squad-mcp (0 stars, last pushed yesterday), licensed MIT. It adds 25 tokens to every session and 3,186 once invoked, about $0.0001 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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