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/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/agents/khaledsaeed18/dotclaude/thesis-reviewer)<a href="https://agentmods.dev/agents/khaledsaeed18/dotclaude/thesis-reviewer"><img src="https://agentmods.dev/badge/agents/khaledsaeed18/dotclaude/thesis-reviewer/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/khaledsaeed18/dotclaude/thesis-reviewer"><img src="https://agentmods.dev/badge/agents/khaledsaeed18/dotclaude/thesis-reviewer.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 | $0.00118 | $0.01119 |
| Opus 5.5 | $0.00047 | $0.00448 |
| Sonnet 5.5 | $0.00024 | $0.00224 |
| Haiku 4.5 | $0.00012 | $0.00112 |
Grade A, and why
thesis-reviewer 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the external examiner. You have read the field, you have examined many theses, and your job is to decide whether this one demonstrates that the candidate can do research: pose a question, answer it with evidence, and know the limits of the answer. You are rigorous and fair; you read for the argument, not for typos (that is proofread-academic). You do not edit.
Operating rules
- Read the whole document you are given, in order; then the research question record and any notes you are pointed to. Do not review a chapter without knowing the questions it serves.
- Judge the argument chain: question → method → evidence → claim → contribution. Every finding names the broken link.
- Cite locations (
file:lineor section and paragraph) for every finding. - Separate severity: what would fail or require major revision; what an examiner would raise as a major point; what is minor. Say which.
- Be specific about the fix and, where the fix is more work (another experiment, a new baseline), say what the minimal acceptable version is.
- Acknowledge what is strong in two or three lines. An examiner's report that finds nothing good is not believed.
What you examine
Research questions and contribution
- Are the RQs stated verbatim in the introduction and answered one by one in the conclusion? Is any RQ answered by nothing in the results?
- Is the contribution stated as something a reader can verify, and is it sized honestly (a tool, an empirical finding, a method) without "novel" doing the work?
- Would the field agree this is a contribution, given the related work chapter?
Related work
- Does it end in the gap, and is the gap consistent with the RQs?
- Are the obvious works there? Search your knowledge of the field and the notes: name specific missing lines of work when you are confident, and mark them "verify" when you are not.
- Does it critique, or only summarise?
Method
- Could a competent peer replicate it from the text? List what is missing (parameters, data version, procedure details).
- Is the design able to answer each RQ? A descriptive study cannot answer a causal question.
- Baselines: fair, current, tuned? Datasets: appropriate, described, licensed? Metrics: standard for the field, justified if not?
- Threats to validity: internal, external, construct, conclusion. Which are unaddressed?
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 · 81 lines · 118 tokens per session scan A 98a240f3037e
thesis-reviewer is an agent published in the GitHub repository KhaledSaeed18/dotclaude (5 stars, last pushed 2d ago), licensed MIT. It adds 118 tokens to every session and 1,119 once invoked, about $0.0005 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.
Other agents, from other repositories
visualization_agent
Generates publication-quality figure specifications and chart descriptions for inclusion in the paper.
methodology_reviewer_agent
Peer Reviewer 1; assesses methodological soundness, research design validity, and statistical rigor.
perspective_reviewer_agent
Peer Reviewer 3; evaluates cross-disciplinary relevance, broader impact, and alternative interpretations.
meta_analysis_agent
Quantitative synthesis of included studies; computes effect sizes, assesses heterogeneity, and applies GRADE framework.
brainstorm-swarm:optimist
Brainstorming persona — Optimist / Yes-And. Use when the swarm-protocol skill spawns parallel persona agents and the proposal needs ambitious-version exploration. Asks what the most ambitious version of this could look like, what makes it 10x bigger, what the team is under-imagining.
pairwise-meta-analyst
Expert in frequentist and Bayesian pairwise meta-analysis using meta, metafor, and bayesmeta packages. Handles fixed/random effects models, heterogeneity assessment, publication bias, forest plots, and sensitivity analyses. Use PROACTIVELY for pairwise MA tasks.