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/luizedupp/rememb/deep-researchnpx skills add LuizEduPP/Rememb --skill deep-researchgit clone --depth 1 https://github.com/LuizEduPP/RemembWhat 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 | $0.00042 | $0.01786 |
| Opus 5 | $0.00021 | $0.00893 |
| Sonnet 5 | $0.00008 | $0.00357 |
| Haiku 4.5 | $0.00004 | $0.00179 |
Grade A, and why
deep-research 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 3d 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 — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Research Skill
This skill provides a systematic approach to conducting thorough research on any topic.
Overview
Enable the AI to perform comprehensive research by:
- Breaking down complex topics into researchable components
- Using multiple information sources (web search, documentation, academic sources)
- Applying critical thinking to synthesize findings
- Presenting well-structured, evidence-based conclusions
When to Use
Activate this skill when users request:
- "Deep research on [topic]"
- "Comprehensive analysis of [subject]"
- "Investigate [topic] thoroughly"
- "Research the latest information about [subject]"
- "Gather detailed information on [topic]"
Example Topics:
- AI agent evaluation metrics and methodologies
- Latest AI/ML news and developments
- Technology stack comparisons
- Market analysis and trends
- Academic literature reviews
- Best practices for specific domains
Research Process
Phase 1: Scoping & Planning
Define Research Objectives:
- Identify core questions to answer
- Determine scope and boundaries
- List key areas to investigate
- Establish success criteria
Plan Information Sources:
- Web search for current information
- Documentation (Context7) for technical details
- Academic/industry sources for authoritative information
- Community resources (GitHub, forums) for practical insights
Phase 2: Information Gathering
Multi-Source Search Strategy:
-
Broad Overview Search
- Use general web search for landscape understanding
- Identify key terms, concepts, and authorities
- Note publication dates for recency
-
Targeted Deep Dives
- Search specific sub-topics identified in overview
- Look for:
- Official documentation
- Academic papers
- Industry reports
- Expert opinions
- Case studies
- Code examples (when relevant)
-
Documentation Lookup
- Use Context7 for library-specific documentation
- Check official API references
- Review changelog and release notes
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.
- 3d ago First seen · 294 lines · 42 tokens per session scan A d3e5276d0140
deep-research is a skill published in the GitHub repository LuizEduPP/Rememb (4 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 1,786 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
tasks
Manage Prismer workspace tasks across the full Kanban lifecycle — create, list, inspect, update, complete, approve, reject, cancel. Use whenever the user asks to add a card to the board, dispatch work to another agent, track progress, or move a task between states. Executes via the cloud task CLI.
agent-coordination
Find other agents, list participants in a conversation, send routed messages, attach files, and recover earlier conversation context (history / resolve a fuzzy reference / read a quoted message / read compressed summaries). Use whenever you need to delegate to another agent, address a peer in a multi-agent…
image-generate
Generate an image from a text prompt via the cloud LLM image proxy, persist it as a content-addressed workspace asset, and return a ContentBlock that downstream renderers can attach. Use whenever the user asks "draw / generate / make an image of …", an agent needs a diagram / illustration as a follow-up artifact, or a…
prismer-im-collab
Coordinate reliably in Prismer conversations, use workspace assets through bounded MCP tools, and keep task work on the board.
claim-agent-ownership
Orchestrator skill for resolving multi-daemon binding contention. Use when you (the orchestrator) detect an agent.binding.contested sync event indicating two daemons are racing for the same agent — explicitly rebind ownership to a chosen target daemon so subsequent dispatches route deterministically. Implements Gap…
human-approval
Request human approval before performing a SAFETY-CRITICAL, IRREVERSIBLE, or SCOPE-EXPANDING action — submit a structured context (action, scope, risk, consequence) plus options, then STOP the current turn. The platform redispatches the agent after the human decides. NEVER use for routine deliverables (writing docs /…