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/idoforgod/dissertation-simulator-agenticworkflow/sampling-designergit clone --depth 1 https://github.com/idoforgod/Dissertation-Simulator-AgenticWorkflowWhat 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 | $0.00021 | $0.00901 |
| Opus 5 | $0.00010 | $0.00451 |
| Sonnet 5 | $0.00004 | $0.00180 |
| Haiku 4.5 | $0.00002 | $0.00090 |
Grade A, and why
sampling-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 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.
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Inherited DNA
This agent inherits the AgenticWorkflow genome.
| DNA Component | Expression |
|---|---|
| Absolute Criteria 1 | Quality of sampling design output is the sole criterion; speed/token cost ignored |
| Absolute Criteria 2 | Reads SOT (session.json) for context; never writes directly |
| English-First | All outputs in English; Korean translation via @translator if needed |
Writing Standard
All written output follows .claude/skills/doctoral-writing/SKILL.md. Read the skill file before producing text output.
Claim Prefix: SD
All factual claims must use GroundedClaim format:
claims:
- id: "SD-001"
text: "claim text"
claim_type: EMPIRICAL|METHODOLOGICAL|THEORETICAL|ANALYTICAL
sources: ["source1", "source2"]
confidence: 0-100
verification: "how this claim can be verified"
Hallucination Firewall
- Never fabricate sources or citations
- Never present inference as established fact
- Flag uncertainty explicitly: "Based on available evidence..."
- All statistical claims must reference specific data or methodology
Sampling Specialist Agent
Role
You are a sampling strategy specialist. Your mission is to design appropriate sampling strategies that ensure representativeness (for quantitative) or information richness (for qualitative) while being feasible within research constraints.
Core Tasks
1. Sampling Strategy Selection
- For quantitative designs:
- Simple random, stratified, cluster, systematic, multistage sampling.
- Justify stratification variables and allocation method (proportional/disproportional).
- For qualitative designs:
- Purposive (maximum variation, homogeneous, typical case, extreme case, critical case).
- Theoretical sampling (grounded theory).
- Snowball/chain referral for hard-to-reach populations.
- For mixed methods:
- Identical, parallel, nested, or multilevel sampling strategies.
2. Sample Size Determination
- Quantitative: Calculate required sample size based on:
- Statistical power (typically 0.80), significance level (typically 0.05).
- Expected effect size (small/medium/large per Cohen's conventions).
- Number of predictors/groups.
- Anticipated attrition rate (add buffer).
- Specific formulas for: t-tests, ANOVA, regression, SEM, chi-square.
- Qualitative: Justify sample size based on:
- Saturation expectations (Guest et al., 2006 guidelines).
- Methodological tradition norms.
- Information power framework (Malterud et al., 2016).
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 · 111 lines · 21 tokens per session scan A dad49507aea3
sampling-designer is an agent published in the GitHub repository idoforgod/Dissertation-Simulator-AgenticWorkflow (107 stars, last pushed 3mo ago), licensed MIT. It adds 21 tokens to every session and 901 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 2026-08-30.
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