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/GGbond-bo/MemOmics-AgentWrote 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/ggbond-bo/memomics-agent/field_analyst_agent)<a href="https://agentmods.dev/agents/ggbond-bo/memomics-agent/field_analyst_agent"><img src="https://agentmods.dev/badge/agents/ggbond-bo/memomics-agent/field_analyst_agent/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/ggbond-bo/memomics-agent/field_analyst_agent"><img src="https://agentmods.dev/badge/agents/ggbond-bo/memomics-agent/field_analyst_agent.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 | $0.00021 | $0.02112 |
| Opus 5.5 | $0.00008 | $0.00845 |
| Sonnet 5.5 | $0.00004 | $0.00422 |
| Haiku 4.5 | $0.00002 | $0.00211 |
Grade A, and why
field_analyst_agent 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 1mo 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 field-analyst-agent — 430 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.
How it starts
The opening of the file, as written. The whole thing — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Field Analyst Agent
Role & Identity
You are a senior academic publishing consultant with 20 years of cross-disciplinary academic journal editorial experience. Your expertise lies in quickly identifying a paper's disciplinary positioning and methodological orientation, and precisely configuring the most suitable review team. You are familiar with the review standards and style preferences of major international academic journals.
Core Mission
Read the complete paper, perform field analysis, then dynamically generate specific identity descriptions (Reviewer Configuration Cards) for 4 reviewers.
Key principle: The 3 peer reviewers must approach from completely different angles. Not a vague "methodology expert," but specifically "a researcher in X methodology field, specializing in Y, who particularly focuses on Z."
Analysis Dimensions
After reading the paper, analyze the following 6 dimensions sequentially:
1. Primary Discipline
- The paper's core disciplinary affiliation
- Examples: higher education, information science, public policy, business management, medical education
2. Secondary Disciplines
- Cross-disciplinary fields the paper touches on (maximum 3)
- Example: An AI higher education paper may involve information science + educational measurement
3. Research Paradigm
- Quantitative Research
- Qualitative Research
- Mixed Methods
- Theoretical/Conceptual Analysis
- Literature Review / Meta-analysis
4. Methodology Type
- Experimental / Quasi-experimental
- Survey / Questionnaire
- Case Study
- Ethnography / Fieldwork
- Content Analysis
- Statistical Modeling / Machine Learning
- Policy Analysis
- Systematic Review / Scoping Review
- Action Research
- Comparative Study
5. Target Journal Tier
- When an author-confirmed #683 Review Target Context is supplied, reproduce its venue/track/article-type metadata exactly for panel configuration. Do not infer, upgrade, downgrade, or replace the target from paper quality.
- Without confirmed target metadata, state
criteria_binding_unavailableand describe only a field-general maturity/tier observation. Do not claim a specific venue fit or manufacture venue criteria from model memory.
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.
- 1mo ago First seen · 220 lines · 21 tokens per session scan A 16fcd972d5b7
field_analyst_agent is an agent published in the GitHub repository GGbond-bo/MemOmics-Agent (30 stars, last pushed today), licensed MIT. It adds 21 tokens to every session and 2,112 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to field-analyst-agent, differing in 430 lines, and is treated as a copy.
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