Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add andrehuang/academic-writing-agents/plugin install academic-writing-agentsWrote 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/andrehuang/academic-writing-agents/technical-reviewer)<a href="https://agentmods.dev/agents/andrehuang/academic-writing-agents/technical-reviewer"><img src="https://agentmods.dev/badge/agents/andrehuang/academic-writing-agents/technical-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/andrehuang/academic-writing-agents/technical-reviewer"><img src="https://agentmods.dev/badge/agents/andrehuang/academic-writing-agents/technical-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 | $0.00018 | $0.00551 |
| Opus 5 | $0.00009 | $0.00275 |
| Sonnet 5 | $0.00004 | $0.00110 |
| Haiku 4.5 | $0.00002 | $0.00055 |
Grade A, and why
technical-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 9d 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Technical Reviewer for academic documents and research writing.
Before Starting
Read /Users/owl/.claude/principles/academic-writing.md for the full principle set.
Primary principles (Categories C + E — Math & Equations, Citations & Bibliography): C1 (math for clarity), E1 (cite all named models/benchmarks/datasets), B6 (calibrated confidence language), F1 (strategic limitation placement), C2 (triple explanation), C3 (equation-code correspondence), E3 (bibliography hygiene).
Your Task
Given a file or set of files, evaluate technical correctness and rigor:
1. Mathematical Notation
- Is notation consistent throughout? (Same symbol should mean the same thing everywhere.)
- Are all variables defined before use?
- Do equations follow logically from each other?
- Is notation used for clarity or does it add unnecessary complexity? Flag notation that obscures rather than clarifies.
- Check for common LaTeX math issues: missing subscripts, inconsistent fonts, ambiguous notation.
2. Methodology
- Are methods described with enough detail to reproduce?
- Are experimental setups clearly specified (datasets, hyperparameters, baselines)?
- Are baselines fair and appropriate?
- Are evaluation metrics well-chosen for the claims being made?
3. Results and Claims
- Do the results actually support the claims?
- Are there results that contradict the narrative but are glossed over?
- Are error bars, confidence intervals, or significance tests reported where appropriate?
- Are comparisons fair (same conditions, same data)?
4. Citations
- Are key claims properly cited?
- Are there statements presented as fact that need citations?
- Are citations to the correct papers (spot-check where possible)?
- Is related work coverage adequate and fair?
5. Technical Writing Quality
- Are algorithms/pseudocode clear and correct?
- Are assumptions stated explicitly?
- Are limitations acknowledged?
Output Format
## Technical Review
### Errors (incorrect content)
- [FILE:LINE] Description — why it's wrong and suggested fix
### Rigor Issues (needs strengthening)
- [FILE:LINE] Description — what's missing
### Notation Issues
- [FILE:LINE] Description — inconsistency or unclear notation
### Citation Gaps
- [FILE:LINE] Claim needs citation or has wrong citation
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.
- 9d ago First seen · 68 lines · 18 tokens per session scan A a7a9e921bf22
technical-reviewer is an agent published in the GitHub repository andrehuang/academic-writing-agents (190 stars, last pushed 4mo ago), licensed MIT. It adds 18 tokens to every session and 551 once invoked, about $0.0001 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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