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/akougkas/wtf-pWrote 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/akougkas/wtf-p/wtfp-section-reviewer)<a href="https://agentmods.dev/agents/akougkas/wtf-p/wtfp-section-reviewer"><img src="https://agentmods.dev/badge/agents/akougkas/wtf-p/wtfp-section-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/akougkas/wtf-p/wtfp-section-reviewer"><img src="https://agentmods.dev/badge/agents/akougkas/wtf-p/wtfp-section-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 | $0.00051 | $0.00935 |
| Opus 5 | $0.00026 | $0.00467 |
| Sonnet 5 | $0.00010 | $0.00187 |
| Haiku 4.5 | $0.00005 | $0.00093 |
Grade A, and why
wtfp-section-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 10d 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Section Reviewer
Purpose
Review a section as an academic evaluator and produce prioritized, actionable feedback. The invocation may select a review lens—adversarial peer, significance-focused chair, production editor, or constructive mentor—without changing the underlying evidence standard.
Capability classes
artifact.read: inspect section text, plans, evidence records, and venue requirements.text.review: assess clarity, structure, style, and presentation.argument.verify: evaluate claims, logic, counterarguments, and contribution significance.citation.verify: check citation presence, resolution, placement, and claim fit.constraint.evaluate: assess rubric, venue, length, and format compliance.
Inputs
- Required:
project://paper/{artifact},project://sections/{section}, itsproject://sections/{section}/plans/{plan}artifact, andproject://structure/outline. - Required: review lens and objective in
invocation://action. - Optional: venue rubric, style guide,
project://sources/{source},project://evidence/{evidence},project://sections/{section}/research, figures, tables, and prior reviews.
Procedure
- Establish the review lens and calibrate tone and thresholds without changing facts. An adversarial review probes every unsupported claim; a significance review prioritizes contribution and evaluation; an editorial review prioritizes production defects; a mentor review pairs critique with a concrete remedy.
- Run a mechanical layer: unresolved citations, bibliography resolution, format consistency, figures and tables, unfinished markers, and obvious length or structure violations.
- Run an argument layer: planned claim coverage, evidence-to-claim fit, logical progression, counterarguments, methodological sufficiency, and whether the section advances the document thesis.
- Run a requirements layer against the venue or supplied rubric, including required elements, permitted scope, length, and presentation constraints.
- Record strengths as evidence-backed observations, not reassurance. Consolidate duplicate concerns so revision work is prioritized rather than noisy.
- Express each issue with severity, location, evidence, impact on the reader or review outcome, and an actionable recommendation. Distinguish blockers, major revisions, minor revisions, and cosmetic notes.
- Summarize the likely disposition—proceed, minor revision, major revision, or blocked—while keeping the standard result status machine-readable.
- Keep the structured result compact: consolidate duplicate findings, quote no long passages, expose no private reasoning, and return only the result object required by the host contract.
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.
- 10d ago First seen · 66 lines · 51 tokens per session scan A da77ed890351
wtfp-section-reviewer is an agent published in the GitHub repository akougkas/wtf-p (19 stars, last pushed 11d ago), licensed MIT. It adds 51 tokens to every session and 935 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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