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 skills add KhaledSaeed18/dotclaude --skill systematic-reviewgit clone --depth 1 https://github.com/KhaledSaeed18/dotclaudeWrote 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/skills/khaledsaeed18/dotclaude/systematic-review)<a href="https://agentmods.dev/skills/khaledsaeed18/dotclaude/systematic-review"><img src="https://agentmods.dev/badge/skills/khaledsaeed18/dotclaude/systematic-review/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/skills/khaledsaeed18/dotclaude/systematic-review"><img src="https://agentmods.dev/badge/skills/khaledsaeed18/dotclaude/systematic-review.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 | $0.00111 | $0.01174 |
| Opus 5.5 | $0.00044 | $0.00470 |
| Sonnet 5.5 | $0.00022 | $0.00235 |
| Haiku 4.5 | $0.00011 | $0.00117 |
Grade A, and why
systematic-review 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 25d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
A systematic review is an empirical study whose data are papers. It is systematic because every decision (what to search, what to include, what to extract) is written down before it is made and applied the same way to every paper. The write-up reports the process with the same care as an experiment reports its procedure.
Phase 1: protocol (before searching)
Write research/slr-protocol.md and have the supervisor agree to it:
- Review questions (RQ1..n), plus the mapping study's classification questions if applicable (which venues, years, methods, evaluation types).
- Scope: the concept boundaries; what is explicitly out.
- Search strategy: databases (ACM DL, IEEE Xplore, Scopus, Web of Science, plus OpenAlex or Semantic Scholar for coverage; arXiv if preprints count), the search string built from the PICO or concept groups with synonyms, the fields searched (title/abstract/keywords), and the date range with the reason. Plan a snowballing round (backward and forward from the included set) and note it.
- Inclusion and exclusion criteria, each testable from title/abstract or full text: language, peer-reviewed venue, primary study, addresses the concept, reports an evaluation. Number them (I1.., E1..).
- Screening procedure: title/abstract then full text; who screens (the student, with a second screener or the supervisor on a 10 to 20% sample); how disagreements are resolved; agreement statistic to report (Cohen's kappa).
- Quality assessment checklist (for an SLR; a mapping study may skip): clear aims, described method, evaluation present, threats discussed, data available. Score, and decide whether low quality excludes or only weights.
- Data extraction form: the fields to capture from each paper (bibliographic, context, method, evaluation, findings relevant to each RQ). One row per paper,
research/slr-extraction.csv. - Synthesis method: narrative synthesis with thematic grouping, vote counting (with its limits stated), or meta-analysis if effects are comparable (rare in CS).
Register the protocol with a date; deviations later are reported as deviations.
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.
- 25d ago First seen · 65 lines · 111 tokens per session scan A fbefe9b24a22
systematic-review is a skill published in the GitHub repository KhaledSaeed18/dotclaude (5 stars, last pushed 2d ago), licensed MIT. It adds 111 tokens to every session and 1,174 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-22.
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