Deepseek Chat
ruvnet/ruflo
One-shot chat completion against DeepSeek's deepseek-chat model via the OpenAI-compatible /v1/chat/completions endpoint.
Diagnose and configure MemSearch memory behavior. An agent skill from zilliztech/memsearch.
$ npx skills add zilliztech/memsearch --skill memory-config -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install zilliztech/memsearch memory-config --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/zilliztech/memsearch.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/codex/skills/memory-config .claude/skills/memory-config && 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 "memory-config" agent skill from https://github.com/zilliztech/memsearch/tree/main/plugins/codex/skills/memory-config into .claude/skills/memory-config/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-config", 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/zilliztech/memsearch/tree/main/plugins/codex/skills/memory-configType 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 zilliztech/memsearch --skill memory-config -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install zilliztech/memsearch memory-config --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zilliztech/memsearch.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/codex/skills/memory-config .agents/skills/memory-config && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "memory-config" agent skill from https://github.com/zilliztech/memsearch/tree/main/plugins/codex/skills/memory-config into .agents/skills/memory-config/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-config", 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 zilliztech/memsearch --skill memory-config -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install zilliztech/memsearch memory-config --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zilliztech/memsearch.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/codex/skills/memory-config .cursor/skills/memory-config && 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 "memory-config" agent skill from https://github.com/zilliztech/memsearch/tree/main/plugins/codex/skills/memory-config into .cursor/skills/memory-config/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-config", 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/zilliztech/memsearch.git --path plugins/codex/skills/memory-config--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 zilliztech/memsearch --skill memory-config -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install zilliztech/memsearch memory-config --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zilliztech/memsearch.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/codex/skills/memory-config .gemini/skills/memory-config && 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 "memory-config" agent skill from https://github.com/zilliztech/memsearch/tree/main/plugins/codex/skills/memory-config into .gemini/skills/memory-config/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-config", 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 zilliztech/memsearch memory-configInstalls 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 zilliztech/memsearch --skill memory-config -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/zilliztech/memsearch.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/codex/skills/memory-config .github/skills/memory-config && 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 "memory-config" agent skill from https://github.com/zilliztech/memsearch/tree/main/plugins/codex/skills/memory-config into .github/skills/memory-config/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-config", 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 zilliztech/memsearch --skill memory-config -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install zilliztech/memsearch memory-config --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zilliztech/memsearch.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/codex/skills/memory-config .opencode/skills/memory-config && 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 "memory-config" agent skill from https://github.com/zilliztech/memsearch/tree/main/plugins/codex/skills/memory-config into .opencode/skills/memory-config/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-config", 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.
memory-configDiagnose and configure MemSearch memory behavior. An agent skill from zilliztech/memsearch.
Memory Config is an agent skill from zilliztech/memsearch. Diagnose and configure MemSearch memory behavior. Use when the user asks about MemSearch configuration, plugin summarization, PROJECT.md/USER.md maintenance, memory directories, index health, provider routing, prompt files, or migration/compatibility questions.
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/claude-code.md`, `references/codex.md` and `references/dsh.md`).
It sits in AI & LLM Engineering, covering Model routing and gateways and Summarization. It works with Milvus and DeepSeek. The repository describes itself as: A persistent, unified memory layer for all your AI agents (e.g. Claude Code, Codex, DSH), backed by Markdown and Milvus. The licence is MIT.
Read from SKILL.md and the folder at commit 2a4652f. 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.
Shell commands in SKILL.md call:
uvgitrgcurlpython3uvxgeminiFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
pypi.orgFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
OPENAI_API_KEYANTHROPIC_API_KEYGEMINI_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Memory Config loads about 2.9k tokens when it runs, and up to ~5.5k if it reads all its reference files. Until then it costs about 69 tokens; SKILL.md has 1,223 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 zilliztech/memsearch at commit 2a4652f, republished under its MIT licence (© zilliztech). 1,223 words, ~2,881 tokens.
.claude/skills/memory-config/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.You are a MemSearch configuration assistant. This skill manages MemSearch settings only. It is not the host agent's built-in memory/config system.
In diagnostic summaries or final answers, state once that this is MemSearch memory configuration, not the host agent's own memory/config system. Do not prepend that sentence to every progress update or every paragraph.
When this skill is triggered, inspect the user's request text. If there is no concrete request, run a diagnostic. If they ask for a specific setting or change, route the request using the flows below.
This skill is shared by five agent platforms, but platform-specific details
(version-check commands, plugins.<platform>.* keys, native model defaults,
restart guidance) live in per-platform reference files. Read ONLY the one file
matching your current environment:
references/claude-code.mdreferences/codex.mdreferences/openclaw.mdreferences/opencode.mdreferences/dsh.mdIf you are unsure which agent you are, check these environment markers:
DSH_HOME/~/.dsh → DeepSeek Harness; CODEX_HOME/~/.codex → Codex;
~/.openclaw → OpenClaw; ~/.config/opencode → OpenCode;
CLAUDE_PLUGIN_ROOT → Claude Code.
Read that platform file before performing platform-specific diagnosis or configuration. Do not read the other platform files.
memory-to-skill skill to review and install candidates.Ask the user before enabling external or paid providers, changing output paths, re-indexing, deleting state, or broadening what gets indexed.
memsearch config list --resolved
memsearch config list --global
memsearch config list --projectCheck the shared CLI version before calling the setup healthy:
memsearch --version
uv tool list --show-paths | rg -n 'memsearch|Package|Installed|path'
curl -fsSL https://pypi.org/pypi/memsearch/json \
| python3 -c 'import json,sys; print(json.load(sys.stdin)["info"]["version"])'If memsearch is unavailable, try uvx --from memsearch[onnx] memsearch --version.
The MemSearch CLI comes from the PyPI package memsearch. Update with
uv tool install -U "memsearch[onnx]" or uv tool upgrade memsearch.
For the host platform's plugin version, update commands, and documentation link, see your platform reference file.
Check memory files:
MDIR="${MEMSEARCH_DIR:-$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.memsearch}/memory"
ls -la "$MDIR"
find "$MDIR" -maxdepth 1 -type f -name '*.md' | sort | tail -10
tail -120 "$MDIR/$(date +%Y-%m-%d).md"Check index health:
memsearch stats
STATE_DIR="${MEMSEARCH_DIR:-$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.memsearch}"
test -f "$STATE_DIR/.index-state.json" && cat "$STATE_DIR/.index-state.json"Some plugin config fields may be missing or empty. That is usually normal:
summarize.enabled, advanced maintenance, and task-specific provider/model fields are newer settings.memsearch config list --resolved, not by reading raw TOML alone.memsearch config init may see more fields than old users because the template includes newer options.Config is resolved from built-in defaults, global config, project config, env refs like env:OPENAI_API_KEY, and runtime env such as MEMSEARCH_DIR.
Use memsearch config list --resolved for effective behavior, --global for global overrides, and --project for repository-specific overrides.
Since v0.4.11, project-local .memsearch.toml is restricted before it is merged.
Only these low-risk local indexing keys are honored from project config:
milvus.collectionembedding.batch_sizechunking.max_chunk_sizechunking.overlap_linesindexing.ignore_filesindexing.excludewatch.debounce_msIndex exclusions are opt-in for compatibility. Missing or empty
indexing.ignore_files and indexing.exclude keep the old scan-all behavior;
new files created by memsearch config init explicitly write
ignore_files = [".gitignore"]. Each directory passed to index/watch is its own
root, and ignore discovery never walks into parent directories.
Trusted settings are ignored or rejected in project config. Put these in global
config (~/.memsearch/config.toml) or pass explicit CLI flags instead:
[llm] and [llm.providers.*][prompts]plugins.<platform>.project_review.enabled,
plugins.<platform>.user_profile.enabled, and
plugins.<platform>.memory_to_skill.enabled (see your platform reference file
for the exact key prefix).Default recommendation:
input_dir / output_file values still resolve inside each current project.Maintenance input_dir and output_file may be relative even when configured globally. They are resolved from the current project directory at runtime, so a global output_file = ".memsearch/PROJECT.md" writes to each project's own .memsearch/PROJECT.md. For custom prompt paths, prefer absolute paths in global config; project prompt paths are not trusted.
The plugin-specific TOML keys (plugins.<platform>.summarize,
plugins.<platform>.project_review, plugins.<platform>.user_profile,
plugins.<platform>.memory_to_skill) and the native summarizer/maintenance
model defaults are in your platform reference file.
provider = "" or native uses the host agent's non-interactive native path (see your platform reference file).[llm.providers.<name>].plugins.<platform>.<task>.model, then named provider model, then built-in default.Common provider examples:
[llm.providers.openai]
type = "openai"
model = "gpt-5-mini"
api_key = "env:OPENAI_API_KEY"
[llm.providers.anthropic]
type = "anthropic"
model = "claude-sonnet-4-6"
api_key = "env:ANTHROPIC_API_KEY"
[llm.providers.gemini]
type = "gemini"
model = "gemini-3-flash-preview"
api_key = "env:GEMINI_API_KEY"Model guidance:
openai -> gpt-5-mini, anthropic -> claude-sonnet-4-6, and gemini -> gemini-3-flash-preview.plugins.<platform>.project_review.model and plugins.<platform>.user_profile.model explicitly.Advanced maintenance runs after the plugin wakes it, only when enabled, journal input changed, and min_interval_hours elapsed. PROJECT.md and USER.md are maintenance artifacts by default and are not automatically indexed.
If indexing seems silent or search looks stale, check .memsearch/.index-state.json
for status, last_error, and failed_files. status: degraded means the
scan completed but one or more files failed; status: error means the index run
did not complete.
If advanced maintenance or memory_to_skill seems silent, check
.memsearch/.maintenance-state.json for <plugin>.<task>.last_error and
last_failed_at; background hook errors may not surface in the chat.
Before enabling advanced maintenance, ask which provider to use, whether the default 24-hour interval is acceptable, whether .memsearch/PROJECT.md / .memsearch/USER.md are acceptable output files, and whether the user wants the enablement global. Do not write plugin automation keys with --project; v0.4.11+ project config ignores or rejects them.
[prompts]
summarize = ""
project_review = ""
user_profile = ""
memory_to_skill = ""Empty prompt paths mean use the built-in MemSearch prompts. Custom prompt files may use {{AGENT_NAME}}, {{TASK_NAME}}, {{PROJECT_DIR}}, {{INPUT_DIR}}, and {{OUTPUT_FILE}}; the runner appends existing output, recent journals, and digest automatically.
Use memsearch config set for changes. For trusted keys such as plugins.*, [llm.providers.*], [prompts], embedding.provider, or milvus.uri, set global config by omitting --project. Use --project only for allowlisted local indexing keys. After changing anything, show the command, the resolved value, and whether a new session is needed.
MemSearch TOML changes are read lazily by the CLI and the plugin's capture/maintenance paths, so values such as plugins.<platform>.summarize.*, plugins.<platform>.project_review.*, plugins.<platform>.user_profile.*, [llm.providers.*], [prompts], milvus.*, and embedding.* usually apply on the next capture, recall, index, or maintenance invocation. See your platform reference file for whether a restart is required after plugin/skill/config file changes. In final diagnostic/change summaries, make clear that this is MemSearch memory configuration, not the host agent's own memory/config system.
When useful, remind the user that they can either continue using this memory-config skill for guided configuration, or manually run memsearch config init for global interactive setup, memsearch config init --project for allowlisted project indexing setup, and memsearch config set/get/list for direct CLI changes.
© zilliztech, 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 5 other files (references) in plugins/codex/skills/memory-config of zilliztech/memsearch.
Open the folder on GitHubat commit 2a4652f
Memory Config 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 |
|---|---|---|---|---|---|---|
| Memory Config this skillzilliztech/memsearch | 2.7k | — | ~2.9k | Automated safety check: Pass | MIT | |
| Deepseek Chatruvnet/ruflo | 74k | — | ~564 | Automated safety check: Notes | MIT | |
| LLM Routerjamesrochabrun/skills | 215 | 1 repos | ~3.3k | Automated safety check: Pass | MIT | |
| New Providerfinch-xu/cc-router | 270 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Configuring Visionoxbshw/watch-skill | 452 | — | ~509 | Automated safety check: Notes | MIT | |
| ClawRouter LLM GatewayBlockRunAI/ClawRouter | 6.6k | — | ~6.8k | Automated safety check: Pass | MIT |
ruvnet/ruflo
One-shot chat completion against DeepSeek's deepseek-chat model via the OpenAI-compatible /v1/chat/completions endpoint.
jamesrochabrun/skills
This skill should be used when users want to route LLM requests to different AI providers (OpenAI, Grok/xAI, Groq, DeepSeek, OpenRouter) using SwiftOpenAI-CLI.
finch-xu/cc-router
用于在 cc-router 仓库新增一个 LLM provider(即在 src-tauri/providers/ 下添加 YAML 描述符并完成配套的同步改动)。当用户说「加 provider」「接入 XX 厂商」「新增订阅源」「provider YAML」「让 cc-router 支持 OpenRouter/Together/Groq/Ollama 之类」时必须触发本…
oxbshw/watch-skill
The user wants to connect an LLM or vision provider, already has an API key, asks "can I use OpenAI/Anthropic/Gemini/OpenRouter", wants local Ollama, or needs different cheap and strong models.
BlockRunAI/ClawRouter
Describes ClawRouter, a local proxy that forwards each LLM request to the blockrun.ai gateway, which routes to a cheaper capable model, paid by USDC wallet or API key credit.
dair-ai/dair-academy-plugins
Has several open-weight models answer a question, rank each other's anonymized answers, then lets a chairman model write the final response through Fireworks AI.
zilliztech/memsearch
Turn workflows from your MemSearch memory into reusable skills.
zilliztech/memsearch
Search and recall relevant memories from past sessions via memsearch.
zilliztech/memsearch
Search and recall relevant memories from past sessions via memsearch.
Categories
Diagnose and configure MemSearch memory behavior. An agent skill from zilliztech/memsearch. Memory Config is an agent skill from zilliztech/memsearch. Diagnose and configure MemSearch memory behavior.
Memory Config fits situations like: the user asks about MemSearch configuration; plugin summarization; PROJECT.md/USER.md maintenance; memory directories.
Run `npx skills add zilliztech/memsearch --skill memory-config -a claude-code`. Or copy the skill folder (plugins/codex/skills/memory-config in zilliztech/memsearch) into .claude/skills/memory-config in your project. Claude Code loads it when a task matches its description.
Run `npx skills add zilliztech/memsearch --skill memory-config -a codex`. Or copy the skill folder (plugins/codex/skills/memory-config in zilliztech/memsearch) into .agents/skills/memory-config 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 zilliztech/memsearch --skill memory-config -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/memory-config, .gemini/skills/memory-config, .github/skills/memory-config and .opencode/skills/memory-config in your project.
Going by SKILL.md and its folder, Memory Config needs the command-line tools its instructions call (uv, git, rg, curl, python3 and uvx) and credentials named OPENAI_API_KEY, ANTHROPIC_API_KEY and GEMINI_API_KEY. Our summary lists: Python 3; A credential in OPENAI_API_KEY; A credential in ANTHROPIC_API_KEY.
SKILL.md names 1 domain. In commands or code: pypi.org; the agent is likely to contact it when it follows the instructions. 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.
Memory Config is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.9k tokens (SKILL.md is roughly 12k 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 2.6k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Memory Config: Deepseek Chat (ruvnet/ruflo, 74k stars), LLM Router (jamesrochabrun/skills, 215 stars), New Provider (finch-xu/cc-router, 270 stars) and Configuring Vision (oxbshw/watch-skill, 452 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
zilliztech (a GitHub organization) maintains it in zilliztech/memsearch, which has 2,723 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on September 24, 2026.
Source: zilliztech/memsearch on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.