research-model-literature

research-model-literature is a skill for Codex from chengziyue1222/math-model-agent. It costs 53 tokens per session (505 once invoked), scanned A, original, MIT.

A research workflow for finding, checking, comparing, and citing papers and datasets used in mathematical models.

In plain words
What is it for?
Use it for literature reviews, parameter sourcing, benchmark and dataset research, research-gap analysis, and verified BibTeX.
Why use it?
It creates a traceable evidence base for modeling decisions and separates verified findings from assumptions and unanswered questions.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Codex.

Good fit Use it for literature reviews, parameter sourcing, benchmark and dataset research, research-gap analysis, and verified BibTeX.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/chengziyue1222/math-model-agent/research-model-literature
Install

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.

Any agent
npx skills add chengziyue1222/math-model-agent --skill research-model-literature
Clone the repo
git clone --depth 1 https://github.com/chengziyue1222/math-model-agent

Made for: Codex.

Wrote 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.

agentmods badge for research-model-literature

README.md
[![agentmods](https://agentmods.dev/badge/skills/chengziyue1222/math-model-agent/research-model-literature/github.svg)](https://agentmods.dev/skills/chengziyue1222/math-model-agent/research-model-literature)
Your own site
<a href="https://agentmods.dev/skills/chengziyue1222/math-model-agent/research-model-literature"><img src="https://agentmods.dev/badge/skills/chengziyue1222/math-model-agent/research-model-literature/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.

agentmods 80×15 button for research-model-literature

Your own site · 80×15
<a href="https://agentmods.dev/skills/chengziyue1222/math-model-agent/research-model-literature"><img src="https://agentmods.dev/badge/skills/chengziyue1222/math-model-agent/research-model-literature.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 505 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00053 $0.00505
Opus 5 $0.00026 $0.00253
Sonnet 5 $0.00011 $0.00101
Haiku 4.5 $0.00005 $0.00051

Measured 11d ago against content hash 7ada3a1b1c2d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

research-model-literature 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 11d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/build_source_record.py, scripts/execute_skill.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/research-model-literature/SKILL.md · 27 lines

How it starts

The opening of the file, as written. The whole thing — 27 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Model Literature

Build a traceable evidence base for modeling choices and parameters.

Workflow

  1. Turn the topic into model, application, data, and validation search concepts.
  2. Search current authoritative sources; prioritize original papers, official datasets, standards, and competition rules.
  3. Search with an identifiable provider and fetch the source or authoritative metadata page. Save candidates explicitly in source_candidates; never inject a problem-specific bibliography from inside a reusable Skill script.
  4. For every candidate record origin (SEARCHED, USER_SUPPLIED, or MANUALLY_ENTERED), retrieval_provider, UTC retrieval_timestamp, source_fetch_status, metadata-verification status/evidence, and content-relevance evidence. USER_SUPPLIED is not equivalent to VERIFIED.
  5. Cluster findings by method and compare assumptions, datasets, metrics, limitations, decision coupling, uncertainty semantics, and validation design. Treat competition exemplars as style/method evidence only: never recover their hidden numerical solution, named entities, or tuned parameters.
  6. Separate established findings, source-supported inference, and open questions.
  7. Validate candidate identities and duplicates with algorithms.modeling_contracts.validate_source_records, then generate BibTeX with records_to_bibtex only from passing records. Record transferable design patterns separately from problem-specific outputs so that a later project cannot inherit an exemplar's answer.

Integrity Rules

Read references/integrity-rules.md before producing citations. Never invent a source, DOI, quotation, result, or BibTeX field. Mark inaccessible or uncertain records as unverified instead of completing them from memory.

Executable Contract

Run scripts/execute_skill.py with model_problem, selected_model, citation_requirements, and the explicit source_candidates file. Emit and register search_queries, search_results, selected_sources, rejected_sources, retrieval_log, metadata_verification, relevance_evidence, literature_evidence, references_bib, and bib_validation. A bibliography without fetched-source provenance and relevance evidence, or generated from hard-coded task sources, is unverified.

Read the full file on GitHub · 27 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 11d ago First seen · 27 lines · 53 tokens per session scan A 7ada3a1b1c2d

Subscribe to this mod's changes

research-model-literature is a skill published in the GitHub repository chengziyue1222/math-model-agent (15 stars, last pushed 1mo ago), licensed MIT. It adds 53 tokens to every session and 505 once invoked, about $0.0003 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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