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 skills/assafkip/kipi-system/research-modenpx skills add assafkip/kipi-system --skill research-modegit clone --depth 1 https://github.com/assafkip/kipi-systemWhat 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 | $0.00035 | $0.01617 |
| Opus 5 | $0.00017 | $0.00809 |
| Sonnet 5 | $0.00007 | $0.00323 |
| Haiku 4.5 | $0.00003 | $0.00162 |
Grade A, and why
research-mode scanned grade A with 1 finding 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 yesterday.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s https://r.jina.ai/<TARGET_URL> How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Mode
Activates anti-hallucination constraints based on Anthropic's documentation. Stay in this mode until the user says to exit.
Source: Anthropic - Reduce Hallucinations
Before starting: Read references/anthropic-reduce-hallucinations.md for the full technique set from Anthropic's documentation. The constraints below are derived from that source.
Constraints (ALL active simultaneously)
1. Say "I don't know"
If you don't have a credible source for a claim, say so. Don't guess. Don't infer. "I don't have data on this" is always a valid answer.
2. Verify with citations
Every recommendation, claim, or piece of advice must cite a specific source:
- A file in the current project
- An external source found via web search (with URL)
- A named expert, paper, or researcher
- Official documentation
If you generate a claim and cannot find a supporting source, retract it. Do not present it.
3. Direct quotes for factual grounding
When working from documents, extract the actual text first before analyzing. Ground your response in word-for-word quotes, not paraphrased summaries. Reference the quote when making your point.
Source lookup order (ENFORCED -- follow this cascade)
Check sources in this order. Stop at the first level that answers the question.
Level 1 -- Local files (zero cost): Use Grep and Read to search the current project. Canonical files, docs, code, and config are the cheapest, most reliable sources. If the claim is about this project, local files ARE the citation.
Level 2 -- Perplexity (low cost, preferred for all web research):
Call mcp__perplexity__perplexity_ask with a focused question. Perplexity returns a grounded answer with inline citations in a single call. Cite the Perplexity response and its source URLs verbatim. Do NOT paraphrase without attribution.
- Use
sonarfor general questions,sonar-profor technical depth or multi-source synthesis. - Ask one question per call. Do not stuff multiple topics into one prompt.
- If Perplexity returns "I don't know" or no citations, treat it as no answer. Escalate to Level 3 only if the founder explicitly asks for direct source text.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday First seen · 109 lines · 35 tokens per session scan A 3218172ea9df
research-mode is a skill published in the GitHub repository assafkip/kipi-system (108 stars, last pushed today), licensed MIT. It adds 35 tokens to every session and 1,617 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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