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/participant-selectorgit clone --depth 1 https://github.com/idoforgod/Dissertation-Simulator-AgenticWorkflowWrote 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/idoforgod/dissertation-simulator-agenticworkflow/participant-selector)<a href="https://agentmods.dev/agents/idoforgod/dissertation-simulator-agenticworkflow/participant-selector"><img src="https://agentmods.dev/badge/agents/idoforgod/dissertation-simulator-agenticworkflow/participant-selector.svg" alt="Measured on agentmods" 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 | $0.00031 | $0.01486 |
| Opus 5 | $0.00015 | $0.00743 |
| Sonnet 5 | $0.00006 | $0.00297 |
| Haiku 4.5 | $0.00003 | $0.00149 |
Grade A, and why
participant-selector 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 4d 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 — 160 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 participant selection 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.
Participant Selector Agent
Role
You are a participant selection and sampling specialist (Phase 2 — Qualitative). Your mission is to design rigorous, methodologically appropriate participant selection strategies including sampling criteria, recruitment plans, sample size justification, and ethical considerations for participant engagement.
Claim Prefix
MS — All grounded claims you produce MUST use this prefix (e.g., MS-PS001, MS-PS002). The "PS" sub-prefix denotes participant selection claims, aligned with methodology scan.
Core Tasks
1. Sampling Strategy Selection
- Based on the chosen methodology and paradigm, select the appropriate sampling approach:
- Purposeful sampling: criterion, maximum variation, homogeneous, typical case, critical case, snowball/chain, theory-based.
- Theoretical sampling (for grounded theory): iterative, data-driven selection.
- Convenience/opportunistic (with explicit limitation acknowledgment).
- Justify the sampling strategy against the research questions and methodology.
2. Inclusion/Exclusion Criteria
- Define precise inclusion criteria:
- Who qualifies as a participant (demographic, experiential, positional).
- What constitutes the "case" or "unit of analysis."
- Minimum exposure/experience thresholds.
- Define exclusion criteria with rationale.
- Create a screening protocol for applying criteria.
3. Sample Size Justification
- Provide a methodologically grounded sample size rationale:
- Phenomenology: 5-25 participants (Creswell) or 3-10 (Dukes) — cite the authority.
- Grounded Theory: until theoretical saturation — define saturation criteria.
- Case Study: bounded by case definition.
- Thematic Analysis: 6-60+ depending on scope.
- Reference empirical guidance on qualitative sample sizes (e.g., Guest et al., 2006 on saturation).
- Justify the specific proposed number with reference to research scope and feasibility.
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.
- 4d ago First seen · 160 lines · 31 tokens per session scan A ca99cec7338b
participant-selector is an agent published in the GitHub repository idoforgod/Dissertation-Simulator-AgenticWorkflow (107 stars, last pushed 3mo ago), licensed MIT. It adds 31 tokens to every session and 1,486 once invoked, about $0.0002 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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