Agent Workflow Designer
borghei/Claude-Skills
Design multi-agent orchestration with workflow DAGs, routing, handoff protocols, and state management.
Managing shared context, memory, and state across multiple agents.
Install State Management
$ npx skills add Owl-Listener/ai-design-skills --skill state-management -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Owl-Listener/ai-design-skills state-management --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/Owl-Listener/ai-design-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/design-agent-orchestration/state-management .claude/skills/state-management && 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 "state-management" agent skill from https://github.com/Owl-Listener/ai-design-skills/tree/main/skills/design-agent-orchestration/state-management into .claude/skills/state-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "state-management", 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/Owl-Listener/ai-design-skills/tree/main/skills/design-agent-orchestration/state-managementType 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 Owl-Listener/ai-design-skills --skill state-management -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Owl-Listener/ai-design-skills state-management --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Owl-Listener/ai-design-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/design-agent-orchestration/state-management .agents/skills/state-management && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "state-management" agent skill from https://github.com/Owl-Listener/ai-design-skills/tree/main/skills/design-agent-orchestration/state-management into .agents/skills/state-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "state-management", 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 Owl-Listener/ai-design-skills --skill state-management -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Owl-Listener/ai-design-skills state-management --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Owl-Listener/ai-design-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/design-agent-orchestration/state-management .cursor/skills/state-management && 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 "state-management" agent skill from https://github.com/Owl-Listener/ai-design-skills/tree/main/skills/design-agent-orchestration/state-management into .cursor/skills/state-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "state-management", 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/Owl-Listener/ai-design-skills.git --path skills/design-agent-orchestration/state-management--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 Owl-Listener/ai-design-skills --skill state-management -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Owl-Listener/ai-design-skills state-management --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Owl-Listener/ai-design-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/design-agent-orchestration/state-management .gemini/skills/state-management && 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 "state-management" agent skill from https://github.com/Owl-Listener/ai-design-skills/tree/main/skills/design-agent-orchestration/state-management into .gemini/skills/state-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "state-management", 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 Owl-Listener/ai-design-skills state-managementInstalls 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 Owl-Listener/ai-design-skills --skill state-management -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Owl-Listener/ai-design-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/design-agent-orchestration/state-management .github/skills/state-management && 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 "state-management" agent skill from https://github.com/Owl-Listener/ai-design-skills/tree/main/skills/design-agent-orchestration/state-management into .github/skills/state-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "state-management", 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 Owl-Listener/ai-design-skills --skill state-management -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Owl-Listener/ai-design-skills state-management --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Owl-Listener/ai-design-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/design-agent-orchestration/state-management .opencode/skills/state-management && 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 "state-management" agent skill from https://github.com/Owl-Listener/ai-design-skills/tree/main/skills/design-agent-orchestration/state-management into .opencode/skills/state-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "state-management", 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.
Facts
- Skill name
state-management- GitHub stars
- 185
- Token cost
- ~1.5k tokens
- SKILL.md length
- 717 words
- Files
- 1
- Skills in repo
- 11
- Repo updated
- First seen
- Licence
- MIT
At a glance
Managing shared context, memory, and state across multiple agents.
- Tasks that involve State management
- SKILL.md covers Types of state, State architecture patterns, Designing state for users and Decision rules, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Tasks that involve Multi-agent orchestration
What it does
State Management is an agent skill from Owl-Listener/ai-design-skills. Managing shared context, memory, and state across multiple agents.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Frontend & Design, covering State management and Multi-agent orchestration. The repository describes itself as: AI Design Skills Collection: agentic skills, commands, and plugins for designing AI products — from interaction patterns to alignment, evaluation, agent orchestration, and prompt… The licence is MIT.
When your agent uses it
- Tasks that involve State management
- Tasks that involve Multi-agent orchestration
Example prompts
- “/state-management”
What it can do on your machine
Read from SKILL.md and the folder at commit f41b650. It shows what the files ask for, not the result of running them.
Tool permissions
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.
Runs code
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.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
State Management loads about 1.5k tokens when it runs. Until then it costs about 21 tokens; SKILL.md has 717 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.
Safety
Auto-check passed
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.
SKILL.md
The full file from Owl-Listener/ai-design-skills at commit f41b650, republished under its MIT licence (© Owl-Listener). 717 words, ~1,537 tokens.
Download SKILL.mdSave it as
.claude/skills/state-management/SKILL.md (or your agent's skills folder).- name
- state-management
- description
- Managing shared context, memory, and state across multiple agents.
State Management
In a multi-agent system, state is the shared truth about what's happened, what's in progress, and what's been decided. Without state management, agents work with stale or conflicting information — and the user pays the cost in repeated questions, contradictory answers, and lost progress.
State management is the plumbing skill of multi-agent design. Get it wrong and every other skill in this plugin gets harder.
Types of state
- Task state: where the overall task is in its lifecycle. Which subtasks are complete, in progress, or pending.
- Context state: what each agent knows. What has been shared, summarised, or dropped.
- User state: preferences, history, and current emotional state.
- Decision state: decisions made, options considered, options rejected (and why).
- Error state: what has failed, been retried, been escalated.
State architecture patterns
- Centralised state: one shared store all agents read from and write to. Simple, debuggable. Bottleneck risk at scale.
- Distributed state: each agent maintains its own state and syncs with others. Flexible. Consistency risk.
- Event-sourced state: state is built from a log of events. Every change is recorded. Auditable. Complex.
- Blackboard pattern: shared workspace where agents post results and read others' contributions. Good for collaborative problem-solving.
Designing state for users
Users have expectations about what the system remembers:
- Within-session state: everything said in this conversation should persist consistently
- Cross-session state: preferences, decisions, and context from past sessions should carry forward
- Cross-agent state: if one agent learned something, other agents should know
- User-controlled state: users should be able to see, edit, and clear what the system remembers
Decision rules
- Default to centralised state. Reach for distributed only when measured cross-agent latency is genuinely the bottleneck. Most teams choose distributed prematurely and pay in consistency bugs forever.
- If a piece of state lives in a single agent's working memory, treat it as lost. Memory across model invocations is unreliable; promote anything that needs to persist to the shared store.
- Cross-session state requires explicit consent per category. "Remember preferences" ≠ "remember what we discussed". Granularity is the design constraint, not a nice-to-have.
- For state conflicts, prefer detection over silent merging. A surfaced conflict the user resolves is recoverable; a silently merged inconsistency is invisible damage.
- State a user can't see, they can't trust. Any state used to personalise behaviour must be visible somewhere the user can find within ~30 s of UI navigation.
Show full SKILL.md (329 more words)Show less
Anti-patterns
- The stale-context bug: an agent acts on state that's been superseded by another agent. Hard to detect because the agent looks correct in isolation. Mitigated by versioning every read.
- The one-source-of-truth fight: two agents both claim authority over the same state slice. Resolution rules are vague. Last write wins, intermittently.
- Implicit state: state lives in an agent's prompt context rather than the shared store. Lost on restart, untransferable, undebuggable.
- State sprawl: schema grows unbounded as features accrete. After six months nobody knows what's used, what's dead, or what's load-bearing.
- Sync deferral: writes are batched for efficiency, then dropped on failure. The user sees "saved" but the state never made it.
- Invisible personalisation: state shapes behaviour the user can't see or override — drift toward manipulation.
When not to use this
- Single-agent products — the model's context window is the state. Reach for
context-window-designinstead. - Stateless transactional features (one-shot completions, image generation calls) — explicit state architecture adds overhead without benefit.
- Prototype phase — premature state architecture freezes choices that should still be loose. Use the simplest possible store, document decisions in
decision-stateonly.
See also
handoff-protocols— context transfer between agents uses the state architecture; design them together.observability-design— state mutations are the most useful traces. Design what's logged at the same time as what's stored.consent-and-agency— cross-session and cross-agent state is consent-laden by default.task-decomposition— task-state schema is determined by the decomposition shape; co-design.
Design Artefacts
- State architecture diagrams (centralised / distributed / event-sourced / blackboard)
- State schema definitions (what's stored, where, by whom, with what TTL)
- State lifecycle specifications (creation, update, archival, deletion)
- Conflict resolution rules per state slice
- User-facing state visibility and control designs
Worked example — task state for a multi-agent customer support flow:
{
"task_id": "tk_8b2",
"owner_agent": "router", // who currently holds the task
"status": "in_progress | escalated | done",
"subtasks": [
{"id": "verify_account", "status": "done", "result_ref": "ctx_a91"},
{"id": "check_refund_eligibility", "status": "in_progress", "owner": "billing_agent"}
],
"user_state_ref": "us_482", // pointer, not embedded copy
"decisions": [
{"at": "...", "by": "router", "choice": "billing_agent", "rejected": ["faq_agent"], "why": "intent: refund"}
],
"errors": [],
"version": 7 // increments on every write; readers check before acting
}The version field is the simplest defence against the stale-context bug. The decisions log with rejected makes the routing legible to humans during incident review.
Adapted from work on shared mental models in multi-agent systems and distributed-systems consistency literature (Lamport on logical clocks; the actor model on isolated state).
© Owl-Listener, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/design-agent-orchestration/state-management of Owl-Listener/ai-design-skills.
Open the folder on GitHubat commit f41b650
Compare with similar skills
State Management 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 |
|---|---|---|---|---|---|---|
| State Management this skillOwl-Listener/ai-design-skills | 185 | — | ~1.5k | Automated safety check: Pass | MIT | |
| Agent Workflow Designerborghei/Claude-Skills | 891 | — | ~2.3k | Automated safety check: Pass | MIT | |
| Onboardingagentuse/agentuse | 205 | — | ~928 | Automated safety check: Pass | Custom licence | |
| Agentic Osaffaan-m/ECC | 276k | 1 repos | ~3.1k | Automated safety check: Notes | MIT | |
| React Generate Skilljiushiwon/wg-skills | 114 | — | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| Agent Collaboration ProtocolLeoYeAI/openclaw-master-skills | 2.2k | — | ~1.1k | Automated safety check: Pass | MIT |
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React Generate Skill
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Agent Collaboration Protocol
LeoYeAI/openclaw-master-skills
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Related
Categories
Questions about State Management
What does State Management do?
Managing shared context, memory, and state across multiple agents. State Management is an agent skill from Owl-Listener/ai-design-skills. Managing shared context, memory, and state across multiple agents.
When should I use State Management?
State Management fits situations like: tasks that involve State management; tasks that involve Multi-agent orchestration.
How do I install State Management in Claude Code?
Run `npx skills add Owl-Listener/ai-design-skills --skill state-management -a claude-code`. Or copy the skill folder (skills/design-agent-orchestration/state-management in Owl-Listener/ai-design-skills) into .claude/skills/state-management in your project. Claude Code loads it when a task matches its description.
How do I install State Management in Codex?
Run `npx skills add Owl-Listener/ai-design-skills --skill state-management -a codex`. Or copy the skill folder (skills/design-agent-orchestration/state-management in Owl-Listener/ai-design-skills) into .agents/skills/state-management in your project. Codex loads it when a task matches its description.
Can I use State Management in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Owl-Listener/ai-design-skills --skill state-management -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/state-management, .gemini/skills/state-management, .github/skills/state-management and .opencode/skills/state-management in your project.
What does State Management need to run?
SKILL.md names no scripts, command-line tools or credentials: State Management is instructions for the agent only.
Does State Management access the network?
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.
Is State Management safe to install?
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.
What licence does State Management use?
State Management is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does State Management use?
About 1.5k tokens (SKILL.md is roughly 6.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to State Management?
Skills that share tags, products or a category with State Management: Agent Workflow Designer (borghei/Claude-Skills, 891 stars), Onboarding (agentuse/agentuse, 205 stars), Agentic Os (affaan-m/ECC, 276k stars) and React Generate Skill (jiushiwon/wg-skills, 114 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains State Management?
Owl-Listener (a GitHub user) maintains it in Owl-Listener/ai-design-skills, which has 185 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on June 9, 2026.
Source: Owl-Listener/ai-design-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.