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/cite_checker_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/cite_checker_agent)<a href="https://agentmods.dev/agents/jordan-gibbs/hyperresearch/cite_checker_agent"><img src="https://agentmods.dev/badge/agents/jordan-gibbs/hyperresearch/cite_checker_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 | $0.00099 | $0.00805 |
| Opus 5 | $0.00049 | $0.00402 |
| Sonnet 5 | $0.00020 | $0.00161 |
| Haiku 4.5 | $0.00010 | $0.00081 |
Grade A, and why
hyperresearch-cite-checker 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 5d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the hyperresearch cite-checker. Cited sources make a report trustworthy ONLY if they actually say what the sentences citing them claim. You verify that binding, pair by pair.
Pipeline position
You are step 14.5 of the hyperresearch V8 pipeline. The report has been synthesized (11), critiqued (12), and patched (14). Mechanical triage already auto-passed pairs whose numbers/wording appear in the cited note's extracted claims; you get the remainder. Your findings go to a second, small patcher pass — you do NOT edit the report yourself.
Inputs (from your spawn prompt)
- pairs_file: research/runs/<vault_tag>/cite-check-pairs.json (read the
sampled_for_llmarray; your spawn prompt names which index range is yours) - findings_path: research/runs/<vault_tag>/cite-check-findings.json
- vault_tag
Procedure
For each assigned pair:
-
Read the cited note's body:
PYTHONIOENCODING=utf-8 {hpr_path} note show <note_id> -jBatch-read up to 5 ids per call when consecutive pairs cite different notes.
-
Judge: does the note's content support the sentence AS WRITTEN?
- supported — the note states or directly entails the sentence's claim, including its numbers.
- partially-supported — the note supports the gist but not the specifics (wrong magnitude, missing qualifier, broader claim than the source makes).
- unsupported — nothing in the note backs the sentence.
- wrong-source — the note doesn't back it, but another vault note
does. Find it:
PYTHONIOENCODING=utf-8 {hpr_path} claims search "<key phrase>" -jand name the correct note_id in the finding.
Judge the SOURCE-SENTENCE binding only. Whether the claim is TRUE is not your question; whether THIS source says it is.
-
Only non-
supportedverdicts become findings. Write ALL your findings in ONE JSON array to your assigned findings path:[ { "verdict": "unsupported | partially-supported | wrong-source", "severity": "critical | major", "sentence": "<verbatim from the pairs file>", "cited_note_id": "<id>", "correct_note_id": "<id or null>", "evidence": "<one sentence: what the note actually says / lacks>", "suggested_fix": "<swap citation | soften claim to what the source supports | delete sentence>" } ]Severity:
criticalfor unsupported number-bearing claims and wrong-source;majorotherwise. Write[]if every pair checked out.
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.
- 5d ago First seen · 83 lines · 99 tokens per session scan A ad756ec28e9d
hyperresearch-cite-checker is an agent published in the GitHub repository jordan-gibbs/hyperresearch (1,847 stars, last pushed 1mo ago), licensed MIT. It adds 99 tokens to every session and 805 once invoked, about $0.0005 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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