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 skills add yogsoth-ai/de-anthropocentric-research-engine --skill design-experimentgit clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engineWrote 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/skills/yogsoth-ai/de-anthropocentric-research-engine/design-experiment)<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/design-experiment"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/design-experiment/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/skills/yogsoth-ai/de-anthropocentric-research-engine/design-experiment"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/design-experiment.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 | $0.00036 | $0.03269 |
| Opus 5.5 | $0.00014 | $0.01308 |
| Sonnet 5.5 | $0.00007 | $0.00654 |
| Haiku 4.5 | $0.00004 | $0.00327 |
Grade A, and why
design-experiment 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 28d 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
design-experiment
Purpose
Translate a falsifiable hypothesis into a statistically defensible experiment. Factorial, ablation, comparison, scaling, and robustness are modes.
When to use / not applicable
Use after a hypothesis has an operational construct and discriminating prediction. Not applicable when the hypothesis or measurable outcome is absent.
Input contract
mode_contracts:
factorial: &experiment_input
required: [falsifiable_hypothesis, outcome, factors, constraints]
optional: [baseline, candidate_models, budget, robustness_axes]
constraints: [analysis_plan_must_be_preregistered]
ablation: *experiment_input
comparison: *experiment_input
scaling: *experiment_input
robustness: *experiment_input
Execution protocol
Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.
- You MUST load skill
identify-variablesto operationalize the outcome, factors, controls, and their functional roles. You MUST load skillenumerate-dimension-valuesto define admissible levels or perturbation values. If the resource envelope or feasibility constraints cannot support an executable design, consideranalyze-constraints-readinessbefore committing to a mode. - Choose
factorial,ablation,comparison,scaling, orrobustnessmode. - You MUST load skill
specify-metricsto preregister metrics, estimands, directionality, and decision thresholds. You MUST load skillestimate-sample-sizeto derive the sample or repetition requirement. You MUST load skillselect-statistical-methodto select the inference or estimation method before observing outcomes; specify power and the stopping rule. If the proposed metric or validator may share artifacts, labels, or assumptions with the system under test, consideraudit-validator-independencebefore freezing the analysis plan. - You MUST load skill
construct-design-matrixto construct the runnable matrix for the selected mode. You MUST load skilldesign-randomness-protocolto define seeds, repetitions, and propagation rules. You MUST load skillspecify-execution-environmentto capture interpretation-relevant hardware, software, data, configuration, and versions. You MUST load skillspecify-reproducibility-protocolto define and test the intended reproduction level. You MUST load skilloptimize-design-under-budgetto select a feasible information-efficient design under the declared resource envelope; include resource and failure checks. Once the design has produced observations and the task changes from planning to inference,analyze-experiment-resultsmay be the better next tactic.
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.
- 28d ago First seen · 162 lines · 36 tokens per session scan A be1ae665521e
design-experiment is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (505 stars, last pushed yesterday), licensed Apache-2.0. It adds 36 tokens to every session and 3,269 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-24.
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