Mem0 Platform SDK
mem0ai/mem0
Adds persistent memory to AI apps with the Mem0 Python and TypeScript SDKs: store, search, update and delete user memories, with framework integrations.
Enhancement overlay for multi-agent / tool-using coder agents.
$ npx skills add agentsope/SkillAlchemy --skill agentsop-tool-scoping -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install agentsope/SkillAlchemy agentsop-tool-scoping --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/agentsope/SkillAlchemy.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/agentsop-tool-scoping .claude/skills/agentsop-tool-scoping && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "agentsop-tool-scoping" agent skill from https://github.com/agentsope/SkillAlchemy/tree/master/skills/agentsop-tool-scoping into .claude/skills/agentsop-tool-scoping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agentsop-tool-scoping", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/agentsope/SkillAlchemy/tree/master/skills/agentsop-tool-scopingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add agentsope/SkillAlchemy --skill agentsop-tool-scoping -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install agentsope/SkillAlchemy agentsop-tool-scoping --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentsope/SkillAlchemy.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/agentsop-tool-scoping .agents/skills/agentsop-tool-scoping && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "agentsop-tool-scoping" agent skill from https://github.com/agentsope/SkillAlchemy/tree/master/skills/agentsop-tool-scoping into .agents/skills/agentsop-tool-scoping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agentsop-tool-scoping", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add agentsope/SkillAlchemy --skill agentsop-tool-scoping -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install agentsope/SkillAlchemy agentsop-tool-scoping --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentsope/SkillAlchemy.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/agentsop-tool-scoping .cursor/skills/agentsop-tool-scoping && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "agentsop-tool-scoping" agent skill from https://github.com/agentsope/SkillAlchemy/tree/master/skills/agentsop-tool-scoping into .cursor/skills/agentsop-tool-scoping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agentsop-tool-scoping", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/agentsope/SkillAlchemy.git --path skills/agentsop-tool-scoping--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add agentsope/SkillAlchemy --skill agentsop-tool-scoping -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install agentsope/SkillAlchemy agentsop-tool-scoping --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentsope/SkillAlchemy.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/agentsop-tool-scoping .gemini/skills/agentsop-tool-scoping && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "agentsop-tool-scoping" agent skill from https://github.com/agentsope/SkillAlchemy/tree/master/skills/agentsop-tool-scoping into .gemini/skills/agentsop-tool-scoping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agentsop-tool-scoping", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install agentsope/SkillAlchemy agentsop-tool-scopingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add agentsope/SkillAlchemy --skill agentsop-tool-scoping -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/agentsope/SkillAlchemy.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/agentsop-tool-scoping .github/skills/agentsop-tool-scoping && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "agentsop-tool-scoping" agent skill from https://github.com/agentsope/SkillAlchemy/tree/master/skills/agentsop-tool-scoping into .github/skills/agentsop-tool-scoping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agentsop-tool-scoping", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add agentsope/SkillAlchemy --skill agentsop-tool-scoping -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install agentsope/SkillAlchemy agentsop-tool-scoping --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentsope/SkillAlchemy.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/agentsop-tool-scoping .opencode/skills/agentsop-tool-scoping && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "agentsop-tool-scoping" agent skill from https://github.com/agentsope/SkillAlchemy/tree/master/skills/agentsop-tool-scoping into .opencode/skills/agentsop-tool-scoping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agentsop-tool-scoping", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
agentsop-tool-scopingEnhancement overlay for multi-agent / tool-using coder agents.
Agentsop Tool Scoping is an agent skill from agentsope/SkillAlchemy. Enhancement overlay for multi-agent / tool-using coder agents. Encodes the per-agent tool- scoping discipline that role-based frameworks (CrewAI, LangChain) document only as a passing best-practice: which agent gets which tool, and why blanket-sharing every tool to every agent is a correctness and blast-radius risk. Activates when an agent system has tools AND there is more than one agent (or one agent holding many tools). Treat a tool as a capability grant; scope by least-privilege. ENHANCE overlay — read…
Its SKILL.md is about 4.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `README.md`, `intermediate/operation_candidates.json` and `references/R1-source-evidence.md`).
It sits in AI & LLM Engineering, covering Building AI agents and Authorization and RBAC. It works with CrewAI and LangChain. The repository describes itself as: From thought to skill. From signal to structure. The licence is MIT.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 6ea799f. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Agentsop Tool Scoping loads about 4.5k tokens when it runs, and up to ~5.7k if it reads all its reference files. Until then it costs about 197 tokens; SKILL.md has 2,172 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from agentsope/SkillAlchemy at commit 6ea799f, republished under its MIT licence (© agentsope). 2,172 words, ~4,507 tokens.
.claude/skills/agentsop-tool-scoping/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.Overlay posture: the base frameworks ([[crewai]], LangChain, LangGraph) all define tools and bind them, but treat scoping as a one-line "assign tools to the agent that needs them" footnote. This overlay makes the rubric first-class. Non-trivial claims cite inline against
references/R1-source-evidence.md.
The lever the base skills under-surface: tool definition and tool binding are
two separate decisions. You define a tool once (reusable class/function), but
you bind it per-agent deliberately. The [[crewai]] SKILL states this in one
clause — "tool 定义可复用;但每个 agent 只绑定其角色匹配的工具"
[crewai-sop §DC-3] — and then moves on. Production failures (wrong-tool
selection, an agent running a destructive op outside its role) come from skipping
the binding decision and defaulting to "give everyone everything."
Activate when any of these hold:
tools=[search, exec, db]
copy-pasted onto every Agent(...), or one bind_tools([...everything]) call
reused for every node. This is the canonical trigger.DELETE, shell exec,
outbound HTTP POST) and you are deciding who may hold it.Do not activate for: a single agent with 1–3 read-only tools (scoping is trivial), or a stateless single LLM call with no tools.
A tool is a capability grant, not a convenience. Binding a tool to an agent is the same act as granting a Unix process a syscall, a service an IAM role, or a container a Linux capability. The discipline is identical and ancient: least-privilege — an agent should hold only the tools its role actually needs.
Three load-bearing consequences:
Definition ≠ binding. Define the tool once (a reusable BaseTool /
function); decide the binding (which agents see it) separately and
minimally. [[crewai]] says "write once, use everywhere" applies to the
definition layer only; the binding layer is per-role [crewai-sop §DC-3].
Every bound tool is in the agent's selection space, and the model pays for it. The LLM must reason over the full tool list on every turn. More tools = bigger schema in context = higher token cost AND lower selection accuracy. This is why a 20-tool agent picks wrong (OP-4, DC-2).
Side-effectful tools change the blast radius of a misfire. A read-only
search tool on the wrong agent wastes tokens. A run_sql or send_payment
tool on the wrong agent (or one with no guard) is a production incident. The
LangGraph HITL discipline — "interrupt on irreversible, high-blast-radius
actions only" — is the runtime half; tool scoping is the design-time half
of the same risk-control [langgraph-sop §Step5].
The mental test before binding any tool to any agent:
"Does THIS role's goal require THIS capability to be exercised by THIS agent autonomously? If a different agent could/should do it, don't bind it here."
A coder agent walks this top-down. Each phase has a gate.
List every tool (name, side-effect class: read | compute | write |
destructive) and every agent (name, one-verb role). If there is exactly one
agent and ≤3 read tools — stop, scoping is trivial.
For each agent, write its role as a single verb (research / analyze / write / review). Then, for each tool, ask the §2 test. Bind only on a "yes."
[crewai-sop §DC-3].Gate: if two agents end up with identical tool sets, ask whether they are really
two roles or one (the [[crewai]] "split-vs-merge" question [crewai-sop §DC-1]).
Any tool classed write or destructive:
interrupt() before the side effect in
LangGraph [langgraph-sop §Step5], or an approval/confirm step in CrewAI.[langgraph-sop §Case4].If any agent now holds >8 tools, selection accuracy degrades (OP-4). Options: split the role, group tools behind a router/sub-agent, or move read-only helpers into the prompt as context instead of tools.
Produce a binding matrix (agents × tools). For each write/destructive cell,
confirm there is exactly one owner and a guard. For each agent, confirm tool
count ≤ limit. This matrix is the security artifact a reviewer reads.
Format: Trigger → Action → Output → Evidence.
tools=[]. Add a tool only when the
role's goal requires that agent to exercise it. Reuse the tool definition
across agents, but bind per-role.Agent(tools=[...]) / per-node bind_tools([...]) holds the
minimal set; a binding matrix.[crewai-sop §DC-3] "每个 agent 只绑定其角色匹配的工具";
[langgraph-sop §Step4] topology binds tools to nodes, not globally.write or destructive operation.[langgraph-sop §Step5] interrupt on irreversible only;
[langgraph-sop §Case4] double-charge from unguarded side effect; cross-link
[[agentsop-llm-tool-idempotency]], [[agentsop-http-tool-wrapping]].tools=registry.all() on every
agent.[crewai-sop §DC-3] definition-reuse vs binding-scope split.[crewai-sop §6.1 AP-1];
see DC-2.context=[...]
(CrewAI) or state (LangGraph).[crewai-sop §DC-3] "reporter=[] (纯综合)".write/destructive
tool bound to >1 agent or lacking a guard; flag any agent over the count limit.[crewai-sop §DC-3] "agent 跨工具滥用 → 收紧工具白名单是最快的 fix".场景: You have web_search, code_executor, db_query and three agents
(researcher / analyst / reporter). The convenient move is
tools=[search, exec, db] on all three.
两条路:
code_executor to "just quickly compute,"
violating role separation; failures become un-localizable (who ran the bad
query?); every agent pays the full 3-tool schema cost every turn.researcher=[search], analyst=[exec, db],
reporter=[]. Clearer responsibilities, localizable errors, smaller per-turn
schema [crewai-sop §DC-3].判断规则:
BaseTool per tool — reuse is good).write tool, your roles
are under-specified — go back to role design [crewai-sop §DC-1].红线: Never let "it's easier to share" be the binding rationale. Ease of wiring is not a capability requirement.
Evidence: [crewai-sop §DC-3], [langgraph-sop §Step4].
场景: A single "do-everything" agent accumulates 20 tools over time. It now
calls delete_record when the user asked to read a record, or burns turns
hopping between near-duplicate tools (search_v1, search_v2, lookup).
陷阱: The instinct is to "improve the prompt" so the model picks better. But
the root cause is the selection space is too large — 20 tool schemas in
context dilute attention and inflate token cost, exactly as ">5 agents" causes
coordination collapse in CrewAI [crewai-sop §6.1 AP-1]. Prompt tweaks paper
over a structural problem.
三条路:
[crewai-sop §DC-1].[langgraph-sop §Step4].判断规则:
红线: A destructive tool on a 20-tool agent is the worst case — high mis-selection probability × high blast radius. Scope it out first.
Evidence: [crewai-sop §6.1 AP-1], [langgraph-sop §Step4/§Case4].
场景: Two agents both "occasionally need" to write to the database.
判断规则:
write/destructive tool gets exactly one owning agent
(single auditable funnel), per OP-2.[langgraph-sop §Step4].红线: Two agents holding the same unguarded destructive tool = two independent ways to cause the same irreversible incident, and an ambiguous audit trail.
Evidence: [langgraph-sop §Step5/§Case4], [crewai-sop §DC-3].
| # | Anti-pattern | Symptom | Fix |
|---|---|---|---|
| AP-1 | Blanket tool sharing (tools=[all] on every agent) | role bleed, un-localizable failures, inflated token cost | per-role binding (OP-1, DC-1) |
| AP-2 | No guard on destructive tools | double-charge / accidental delete on retry or mis-selection | single owner + HITL + idempotency (OP-2, [[agentsop-llm-tool-idempotency]]) |
| AP-3 | One mega-agent with 20 tools | wrong-tool selection, tool-hopping, cost | cap ≤8, split or route (OP-4, DC-2) |
| AP-4 | Prompt-patching tool misuse | "please don't use X" in backstory | remove the tool from the binding (OP-7) |
| AP-5 | Sharing the destructive tool itself instead of the definition | two paths to the same incident | extract single-owner writer (DC-3) |
| AP-6 | Binding tools to synthesis agents | writer/reporter "wanders" into search/exec | bind zero tools (OP-5) |
Boundaries — this overlay does NOT cover:
[langgraph-sop §Step5].The scoping decision is universal; only the binding syntax differs.
| Framework | Define a tool | Bind per-agent (the scoping point) | Scoping notes |
|---|---|---|---|
| CrewAI | BaseTool subclass / @tool | Agent(role=..., tools=[search]) — per agent | Definition reusable, binding per-role [crewai-sop §DC-3]. allow_delegation further widens effective capability — keep it False on workers [crewai-sop §DC-5]. |
| LangGraph | a callable / @tool | model.bind_tools([...]) per node, or per create_react_agent | Tools bound to the node that needs them, not globally; topology decides who routes to the tool-bearing node [langgraph-sop §Step2/§Step4]. Guard destructive tools with interrupt() [langgraph-sop §Step5]. |
| LangChain (agents) | @tool / Tool | tools list passed to each AgentExecutor | Same definition-vs-binding split; the base LangChain docs note "give the agent the tools it needs" but leave the per-agent rubric implicit — this overlay fills that gap. |
| OpenAI Assistants | tools=[{type/function...}] | per-Assistant tools array | Each Assistant is a scoping boundary; create role-specific Assistants rather than one with every function. |
| Claude tool_use | tools=[{name, input_schema}] in the API call | the tools list of a given request/agent | Scope by sending only the tools relevant to that agent's turn; large tool lists raise mis-selection and token cost identically. |
One-line cross-walk: CrewAI agent.tools ≈ LangGraph per-node
bind_tools ≈ Assistant tools array ≈ Claude request tools — in every case,
the right-hand list is the capability grant, and least-privilege says keep it
minimal.
| web_search | run_sql (write) | send_email (write) | code_exec |
--------------+------------+-----------------+--------------------+-----------+
researcher | ✓ | · | · | · |
analyst | · | · | · | ✓ |
db_writer* | · | ✓ (HITL) | · | · |
notifier* | · | · | ✓ (HITL) | · |
reporter | · | · | · | · | ← zero-tool synthesis
--------------+------------+-----------------+--------------------+-----------+
* single owner of a destructive tool; guarded + idempotentAudit rule: every (write) column has exactly one ✓, and it is (HITL).
[crewai-sop] = crewai-sop-skill/SKILL.md (per-agent tools §DC-3; split §DC-1; delegation §DC-5; scaling AP-1)[langgraph-sop] = langgraph-sop-skill/SKILL.md (bind_tools to nodes §Step2/4; HITL §Step5; double-charge §Case4)[[crewai]], [[agentsop-http-tool-wrapping]], [[agentsop-llm-tool-idempotency]] — sibling overlaysreferences/R1-source-evidence.md© agentsope, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 3 other files (references) in skills/agentsop-tool-scoping of agentsope/SkillAlchemy.
Open the folder on GitHubat commit 6ea799f
Agentsop Tool Scoping next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Agentsop Tool Scoping this skillagentsope/SkillAlchemy | 459 | — | ~4.5k | Automated safety check: Pass | MIT | |
| Mem0 Platform SDKmem0ai/mem0 | 67k | 2 repos | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| Edgeone Makers MigrationTencentEdgeOne/edgeone-makers-tools | 1.9k | 1 repos | ~4.1k | Automated safety check: Pass | MIT | |
| Omnigent Framework Detectionomnigent-ai/omnigent | 11k | — | ~610 | Automated safety check: Pass | Apache-2.0 | |
| Crewai Multi AgentOrchestra-Research/AI-Research-SKILLs | 13k | 2 repos | ~3.4k | Automated safety check: Pass | MIT | |
| Agent Governancegithub/awesome-copilot | 40k | 2 repos | ~4.6k | Automated safety check: Pass | MIT |
mem0ai/mem0
Adds persistent memory to AI apps with the Mem0 Python and TypeScript SDKs: store, search, update and delete user memories, with framework integrations.
TencentEdgeOne/edgeone-makers-tools
Migrate existing AI agent projects (LangChain, LangGraph, OpenAI Agents SDK, Claude Agent SDK, CrewAI) to EdgeOne Makers platform conventions.
omnigent-ai/omnigent
Scans Python agent code for framework imports and recommends the matching Omnigent executor type, or says when the framework is not natively supported yet.
Orchestra-Research/AI-Research-SKILLs
Multi-agent orchestration framework for autonomous AI collaboration.
github/awesome-copilot
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems.
TencentCloudBase/CloudBase-AI-Toolkit
Build and deploy AI agents with CloudBase Agent SDK (TypeScript & Python).
agentsope/SkillAlchemy
SOP for terminal-based, git-native AI pair programming with Aider (git work-tree + tree-sitter repo-map + edit-format + human-in-loop REPL).
agentsope/SkillAlchemy
Coder-agent working-file budget discipline: keep the editable working set (files you /add into writable context) under ~25k tokens, separate "read" from "edit", delegate breadth to a read-only…
agentsope/SkillAlchemy
Split a multi-call LM workflow by cognitive load, not by accuracy: let one strong model make the few reasoning decisions and a cheap model do the many mechanical executions (Aider architect+editor…
agentsope/SkillAlchemy
SOP for building multi-agent systems with CrewAI — role-based collaboration, sequential/hierarchical processes, Flows, memory, delegation.
agentsope/SkillAlchemy
SOP for building LLM applications on Dify — visual workflow + chatflow + agent + RAG knowledge base + plugin marketplace + observability, self-hostable.
agentsope/SkillAlchemy
Designs multiscale chunking for RAG by embedding small units for retrieval precision and returning larger context for synthesis.
Categories
Enhancement overlay for multi-agent / tool-using coder agents. Agentsop Tool Scoping is an agent skill from agentsope/SkillAlchemy. Enhancement overlay for multi-agent / tool-using coder agents.
Agentsop Tool Scoping fits situations like: tasks that involve Building AI agents; tasks that involve Authorization and RBAC.
Run `npx skills add agentsope/SkillAlchemy --skill agentsop-tool-scoping -a claude-code`. Or copy the skill folder (skills/agentsop-tool-scoping in agentsope/SkillAlchemy) into .claude/skills/agentsop-tool-scoping in your project. Claude Code loads it when a task matches its description.
Run `npx skills add agentsope/SkillAlchemy --skill agentsop-tool-scoping -a codex`. Or copy the skill folder (skills/agentsop-tool-scoping in agentsope/SkillAlchemy) into .agents/skills/agentsop-tool-scoping in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add agentsope/SkillAlchemy --skill agentsop-tool-scoping -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agentsop-tool-scoping, .gemini/skills/agentsop-tool-scoping, .github/skills/agentsop-tool-scoping and .opencode/skills/agentsop-tool-scoping in your project.
SKILL.md names no scripts, command-line tools or credentials: Agentsop Tool Scoping is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Agentsop Tool Scoping is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.5k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.2k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Agentsop Tool Scoping: Mem0 Platform SDK (mem0ai/mem0, 67k stars), Edgeone Makers Migration (TencentEdgeOne/edgeone-makers-tools, 1.9k stars), Omnigent Framework Detection (omnigent-ai/omnigent, 11k stars) and Crewai Multi Agent (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
agentsope (a GitHub user) maintains it in agentsope/SkillAlchemy, which has 459 GitHub stars. The repository holds 45 skills in this directory. The repository was last updated on September 2, 2026.
Source: agentsope/SkillAlchemy on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.