sr-search-record

sr-search-record is a skill for Claude Code, Codex from qiaomiaojoe/ai-academic-workflow. It costs 350 tokens per session (7,761 once invoked), scanned A, original, no licence file.

An automated literature-review search and screening workflow using OpenAlex, an open database and API for scholarly research, and Zotero, a reference manager.

In plain words
What is it for?
It is for preparing systematic, semi-systematic, narrative, or integrative reviews: creating search records, inclusion and exclusion tables, a selection-flow count, a Zotero library, and a list for human checking.
Why use it?
It organizes repeated searches, removes duplicates, narrows papers by abstract relevance, and records which studies were included or excluded. It also identifies papers missed by the initial search through citation tracking.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit It is for preparing systematic, semi-systematic, narrative, or integrative reviews: creating search records, inclusion and exclusion tables, a selection-flow count, a Zotero library, and a list for human checking.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/qiaomiaojoe/ai-academic-workflow/sr-search-record
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 qiaomiaojoe/ai-academic-workflow --skill sr-search-record
Clone the repo
git clone --depth 1 https://github.com/qiaomiaojoe/ai-academic-workflow

Made for: Claude Code, 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 sr-search-record

README.md
[![agentmods](https://agentmods.dev/badge/skills/qiaomiaojoe/ai-academic-workflow/sr-search-record/github.svg)](https://agentmods.dev/skills/qiaomiaojoe/ai-academic-workflow/sr-search-record)
Your own site
<a href="https://agentmods.dev/skills/qiaomiaojoe/ai-academic-workflow/sr-search-record"><img src="https://agentmods.dev/badge/skills/qiaomiaojoe/ai-academic-workflow/sr-search-record/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 sr-search-record

Your own site · 80×15
<a href="https://agentmods.dev/skills/qiaomiaojoe/ai-academic-workflow/sr-search-record"><img src="https://agentmods.dev/badge/skills/qiaomiaojoe/ai-academic-workflow/sr-search-record.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 350 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,761 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 unknown 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 $0.00350 $0.07761
Opus 5 $0.00175 $0.03880
Sonnet 5 $0.00070 $0.01552
Haiku 4.5 $0.00035 $0.00776

Measured 11d ago against content hash a6ad74249f58, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

sr-search-record 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 1 executable file (scripts/oa_search.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/sr-search-record/SKILL.md · 273 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

Files

What ships with it

1 file 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 · 273 lines · 350 tokens per session scan A a6ad74249f58

Subscribe to this mod's changes

sr-search-record is a skill published in the GitHub repository qiaomiaojoe/ai-academic-workflow (7 stars, last pushed 1mo ago), with no licence file. It adds 350 tokens to every session and 7,761 once invoked, about $0.0018 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 2026-08-31.

Related

Other skills, from other repositories

analyze-stats

Statistical analysis for medical research papers. Generates reproducible Python/R code with publication-ready tables and figures. Supports diagnostic accuracy, inter-rater agreement, meta-analysis, survival analysis, survey data, group comparisons, regression, propensity score, and repeated measures.

Aperivue/medsci-skills · 56 tokens

self-review

Pre-submission self-review for the user's own manuscripts, applying a reviewer perspective. Systematic check across 10 categories with research-type branching. Outputs Anticipated Major/Minor Comments with severity framing and optional R0 numbering for /revise pipeline integration.

Aperivue/medsci-skills · 54 tokens

make-figures

Generate publication-ready figures and visual abstracts for medical research papers. Supports ROC curves, forest plots, CONSORT/STARD/PRISMA flow diagrams, calibration plots, Kaplan-Meier curves, Bland-Altman plots, confusion matrices, pipeline diagrams, and journal-specific visual/graphical abstracts (python-pptx…

Aperivue/medsci-skills · 71 tokens

meta-analysis

Systematic review and meta-analysis pipeline for medical research. Covers protocol registration (PROSPERO), search strategy, screening, data extraction, risk of bias assessment (QUADAS-2/ROBINS-I), statistical synthesis (bivariate/HSROC for DTA, random-effects for intervention), and PRISMA-compliant reporting.…

Aperivue/medsci-skills · 80 tokens

present-paper

Academic presentation preparation — paper-driven (journal club, grand rounds, seminar) and lecture/teaching decks (course material, workshop slides, conference talks). Analyzes source material, finds supporting references, drafts audience-adapted speaker scripts, generates or augments PPTX with speaker notes, and…

Aperivue/medsci-skills · 67 tokens

write-paper

Full-pipeline medical/scientific paper writing. 8-phase IMRAD workflow from outline to submission-ready manuscript. Supports original articles, case reports, case series, meta-analyses, AI validation studies, animal studies, and technical notes. Do NOT trigger for self-checking (use self-review instead).

Aperivue/medsci-skills · 65 tokens