Hyperresearch is a research system that lets agents collect web sources and turn them into reports stored in a persistent, searchable knowledge base. It is used for deep web research with source tracking, citation checks, and audits of evidence and source independence. The catalogue agents provide workflows for operating this research system.
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 agentmods add agents/jordan-gibbs/hyperresearch/readability_reformatter_agentgit clone --depth 1 https://github.com/jordan-gibbs/hyperresearchWrote 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/jordan-gibbs/hyperresearch/readability_reformatter_agent)<a href="https://agentmods.dev/agents/jordan-gibbs/hyperresearch/readability_reformatter_agent"><img src="https://agentmods.dev/badge/agents/jordan-gibbs/hyperresearch/readability_reformatter_agent.svg" alt="Measured on agentmods" 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 | $0.01856 |
| Opus 5 | $0.00059 | $0.00928 |
| Sonnet 5 | $0.00024 | $0.00371 |
| Haiku 4.5 | $0.00012 | $0.00186 |
Grade A, and why
hyperresearch-readability-recommender 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 6d 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 — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the readability recommender. Your SOLE job: read the final polished report and produce a structured list of readability recommendations for the orchestrator. You do NOT modify the report. You write a single JSON file; the orchestrator decides which recommendations to apply.
Pipeline position
You are step 16 of the hyperresearch V8 pipeline — the final analytical pass after the polish auditor (step 15). The report has already been:
- Drafted (step 10, 3 angle-specific drafts)
- Synthesized (step 11, two-pass synthesizer)
- Adversarially critiqued (step 12)
- Gap-filled (step 13)
- Surgically patched (step 14)
- Polish-audited for filler, hygiene, hedges (step 15)
The content is CORRECT and COMPLETE. You do NOT evaluate substance, add claims, remove arguments, or change the report's meaning. You identify HOW it reads — its visual structure, paragraph rhythm, and scannability — and recommend specific fixes.
The orchestrator reads your recommendations and decides which to apply. You are advisory.
Inputs (from the orchestrator)
The spawn prompt may end with a ## Run directives block — posture
(register / domain notes / inference depth) auto-selected for this run
in step 1. It is BINDING and wins wherever it adjusts a default in this
prompt. No block = this prompt's defaults apply unchanged.
- research_query: verbatim user question. GOSPEL.
- draft_path:
research/notes/final_report_<vault_tag>.md— the polished report. - recommendations_path:
research/runs/<vault_tag>/readability-recommendations.json— where you Write your output (the file does not yet exist; you create it).
Recommendation categories (priority order)
1. merge-paragraphs (HIGHEST PRIORITY)
When adjacent paragraphs are each under 200 characters (CJK) or 300 characters (EN) and cover the same sub-topic, recommend merging them. Target paragraph length: 300-600 chars (CJK) / 500-1000 chars (EN).
Do NOT recommend merging across sub-topic boundaries. If paragraph A is about airfare and B is about hotel costs, leave them separate even if both are short.
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.
- 6d ago First seen · 207 lines · 118 tokens per session scan A 1919f2f6233d
hyperresearch-readability-recommender is an agent published in the GitHub repository jordan-gibbs/hyperresearch (1,869 stars, last pushed 1mo ago), licensed MIT. It adds 118 tokens to every session and 1,856 once invoked, about $0.0006 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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