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 skills add assafkip/kipi-system --skill research-modegit clone --depth 1 https://github.com/assafkip/kipi-systemWrote 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/skills/assafkip/kipi-system/research-mode)<a href="https://agentmods.dev/skills/assafkip/kipi-system/research-mode"><img src="https://agentmods.dev/badge/skills/assafkip/kipi-system/research-mode/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/skills/assafkip/kipi-system/research-mode"><img src="https://agentmods.dev/badge/skills/assafkip/kipi-system/research-mode.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00035 | $0.01617 |
| Opus 5.5 | $0.00014 | $0.00647 |
| Sonnet 5.5 | $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 1mo 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.
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.
- 1mo ago First seen · 109 lines · 35 tokens per session scan A 3218172ea9df
research-mode is a skill published in the GitHub repository assafkip/kipi-system (121 stars, last pushed 2d ago), licensed MIT. It adds 35 tokens to every session and 1,617 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other skills, from other repositories
format
MIF (Modeled Information Format) 1.4.2 Level 3 memory templates and formatting guidelines.
core
This skill should be used when the user says "capture memory", "save to memory", "remember this", or trigger phrases like: "I've decided", "let's use", "we're going with", "I learned", "turns out", "TIL", "discovered", "I'm stuck", "blocked by", "always use", "never do", "convention is". Also triggers on recall…
custodian
Memory system custodian for health checks, validation, and maintenance. Trigger phrases: "check memory health", "validate memories", "fix broken links", "update decay", "relocate memories", "audit memories", "memory maintenance", "custodian", "memory health".
blackboard
Cross-session handoff, persistent context via blackboard, and agent coordination patterns.
ontology
Ontology-based entity discovery and validation for mnemonic memories. Define custom namespaces, entity types, traits, and relationships. Triggers: "entity discovery", "validate ontology", "define namespaces", "resolve entity references", "list ontologies", "show namespaces", "entity types", "entity relationships"…
search
This skill should be used when the user says "search memories", "find in memories", "grep mnemonic", "look for memory", "deep search", "synthesize knowledge", or asks questions like "what do we know about X". Provides progressive disclosure and enhanced iterative search with synthesis.