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/skill-lookupnpx skills add LuizEduPP/Rememb --skill skill-lookupgit clone --depth 1 https://github.com/LuizEduPP/RemembWrote 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/luizedupp/rememb/skill-lookup)<a href="https://agentmods.dev/skills/luizedupp/rememb/skill-lookup"><img src="https://agentmods.dev/badge/skills/luizedupp/rememb/skill-lookup.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 | $0.00050 | $0.00681 |
| Opus 5 | $0.00025 | $0.00341 |
| Sonnet 5 | $0.00010 | $0.00136 |
| Haiku 4.5 | $0.00005 | $0.00068 |
Grade A, and why
skill-lookup 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 4d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Lookup
Overview
Use this skill to search a skill registry, inspect candidate skills, and install selected skills into a concrete <skill-root> without assuming a specific assistant or editor.
When to Use
Use this skill when the user wants to:
- find an existing skill before building one
- browse a registry by topic, category, or tag
- inspect the files included in a skill
- install a skill into a local or project skill directory
Core Workflow
- Search the registry with
search_skillsusing the user's task, domain, and likely triggers. - Present concise results with title, description, author, and file summary.
- If the user selects a candidate, fetch the full package with
get_skill. - Ask for or infer the target
<skill-root>for installation. - Save
SKILL.mdand any companion files under<skill-root>/{slug}/. - Verify that the saved
SKILL.mdis present and that the frontmatter is intact. - Explain what the installed skill does and when it should activate.
Available Tools
search_skills: Search for skills by keyword, category, or tagget_skill: Retrieve one skill with all files and metadata
Inputs / Assumptions
queryshould reflect the user's actual problem, not just a generic domain labellimitshould stay small enough to review meaningfullycategoryandtagfilters are optional refinements, not mandatory inputs- Installation should use a real
<skill-root>chosen for the current environment
Examples
Example search
search_skills({"query": "code review", "limit": 5, "category": "coding"})
Example retrieval
get_skill({"id": "abc123"})
Example installation layout
<skill-root>/skill-slug/
├── SKILL.md
├── reference.md
└── scripts/
Optional Host Notes
- Some environments expose separate user-level and workspace-level skill roots. Treat that as a deployment choice rather than a requirement of the skill itself.
- Some environments refresh skills automatically, while others need reload, reindex, or restart before a new installation becomes visible.
- If the user explicitly asks for host-specific installation steps, provide them after the generic workflow is clear.
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.
- 4d ago First seen · 92 lines · 50 tokens per session scan A 68eb38e6e8e7
skill-lookup is a skill published in the GitHub repository LuizEduPP/Rememb (4 stars, last pushed 1mo ago), licensed MIT. It adds 50 tokens to every session and 681 once invoked, about $0.0003 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
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recall
Recall this repository's OwnMem local memory before changing code, and keep it healthy. Use when a repository contains .ownmem/, when past debugging lessons could apply ("have we hit this before", "why is it done this way"), or when the user mentions ownmem, project memory, or recalling across sessions.
init
Install or update OwnMem in the current repository. Use when the user asks to set up OwnMem, add local project memory for coding agents, or refresh an existing OwnMem installation after a version bump.
honcho-integration
Integrate Honcho memory into existing Python or TypeScript codebases. Use when adding Honcho SDK, setting up peers, configuring sessions, and accessing Honcho's representation.
honcho-memory
Concepts and strategy for using a connected Honcho as persistent memory of the user — the recall/record loop and session and peer design. Start here to understand how Honcho memory works, then connect — via a first-class integration for your environment if one exists (preferred), or raw MCP tools (covered here) or the…
verify
Build, launch, and drive a local Honcho stack to verify a change at its runtime surface (the /v3 HTTP API and the deriver queue). Use when verifying a diff or confirming a change works in the running app.