MCP Server Builder
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
Health and optimization stats for SuperLocalMemory — call slmoptimizestats() for live compression and cache counters (compressruns, tokenssavedcompress, cacheproxyhits, cacheproxymisses…
$ npx skills add qualixar/superlocalmemory --skill slm-status -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install qualixar/superlocalmemory slm-status --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/qualixar/superlocalmemory.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugin/skills/slm-status .claude/skills/slm-status && 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 "slm-status" agent skill from https://github.com/qualixar/superlocalmemory/tree/main/plugin/skills/slm-status into .claude/skills/slm-status/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "slm-status", 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/qualixar/superlocalmemory/tree/main/plugin/skills/slm-statusType 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 qualixar/superlocalmemory --skill slm-status -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install qualixar/superlocalmemory slm-status --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/qualixar/superlocalmemory.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugin/skills/slm-status .agents/skills/slm-status && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "slm-status" agent skill from https://github.com/qualixar/superlocalmemory/tree/main/plugin/skills/slm-status into .agents/skills/slm-status/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "slm-status", 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 qualixar/superlocalmemory --skill slm-status -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install qualixar/superlocalmemory slm-status --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/qualixar/superlocalmemory.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugin/skills/slm-status .cursor/skills/slm-status && 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 "slm-status" agent skill from https://github.com/qualixar/superlocalmemory/tree/main/plugin/skills/slm-status into .cursor/skills/slm-status/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "slm-status", 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/qualixar/superlocalmemory.git --path plugin/skills/slm-status--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 qualixar/superlocalmemory --skill slm-status -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install qualixar/superlocalmemory slm-status --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/qualixar/superlocalmemory.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugin/skills/slm-status .gemini/skills/slm-status && 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 "slm-status" agent skill from https://github.com/qualixar/superlocalmemory/tree/main/plugin/skills/slm-status into .gemini/skills/slm-status/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "slm-status", 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 qualixar/superlocalmemory slm-statusInstalls 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 qualixar/superlocalmemory --skill slm-status -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/qualixar/superlocalmemory.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugin/skills/slm-status .github/skills/slm-status && 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 "slm-status" agent skill from https://github.com/qualixar/superlocalmemory/tree/main/plugin/skills/slm-status into .github/skills/slm-status/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "slm-status", 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 qualixar/superlocalmemory --skill slm-status -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install qualixar/superlocalmemory slm-status --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/qualixar/superlocalmemory.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugin/skills/slm-status .opencode/skills/slm-status && 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 "slm-status" agent skill from https://github.com/qualixar/superlocalmemory/tree/main/plugin/skills/slm-status into .opencode/skills/slm-status/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "slm-status", 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.
slm-statusHealth and optimization stats for SuperLocalMemory — call slmoptimizestats() for live compression and cache counters (compressruns, tokenssavedcompress, cacheproxyhits, cacheproxymisses…
Slm Status is an agent skill from qualixar/superlocalmemory. Health and optimization stats for SuperLocalMemory — call slmoptimizestats() for live compression and cache counters (compressruns, tokenssavedcompress, cacheproxyhits, cacheproxymisses, cachekvhits, cachekvmisses); run slm status [--json] for system state (mode, profile, DB size, fact/entity/edge counts) and slm doctor [--json] for preflight including the "Optimize (Surface B)" health line; use together to confirm optimization is actually saving tokens.
Its SKILL.md is about 2.4k 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 Agent Workflows. The repository describes itself as: Open-source governed, local-first memory control plane for AI agents and teams. arXiv:2608.08253. The licence is AGPL-3.0.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 26f8c68. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
slm_optimize_statsget_statusget_brain_evidence_statusBashFrom allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash, python and json).
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.
Slm Status loads about 2.4k tokens when it runs. Until then it costs about 121 tokens; SKILL.md has 989 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 noted patterns worth knowing about, such as sudo or a known installer.
allowed-tools: slm_optimize_stats, get_status, get_brain_evidence_status, BashAutomated 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 qualixar/superlocalmemory at commit 26f8c68, republished under its AGPL-3.0 licence (© qualixar). 989 words, ~2,409 tokens.
.claude/skills/slm-status/SKILL.md (or your agent's skills folder).Use this skill to answer: "Is SLM healthy?", "Is compression/caching actually saving tokens?", and "What does the system look like right now?" It covers the MCP stats and status tools, the slm status CLI, the slm doctor preflight, and the store-health commands.
slm_optimize_stats() -> dictNo arguments. Returns the counters the daemon has persisted.
| Key | Type | Meaning |
|---|---|---|
ok | bool | True on success; False on internal error |
compress_runs | int | Total compress calls recorded by the daemon (persisted across restarts) |
tokens_saved_compress | int | Cumulative tokens saved by compression (daemon-persisted) |
cache_proxy_hits | int | Proxy-layer cache hits (daemon-persisted) |
cache_proxy_misses | int | Proxy-layer cache misses (daemon-persisted) |
cache_kv_hits | int | Hits on the slm_cache_get key-value cache (daemon-persisted) |
cache_kv_misses | int | Misses on the slm_cache_get key-value cache (daemon-persisted) |
ccr_note | str | None | Note about CCR entry count (not tracked per-session; see daemon /api/v1/metrics) |
note | str | None | Scope clarification or error detail |
All six counters are daemon-persisted: they survive MCP restarts and accumulate over the install's lifetime, so they are totals, not per-session figures. Only if the persisted KV counters cannot be read does the tool fall back to this process's own tally (the note field says so). To judge one stretch of work, call slm_optimize_stats before and after and subtract.
stats = await slm_optimize_stats()
if stats["ok"]:
savings = stats["tokens_saved_compress"]
kv_hit_rate = (
stats["cache_kv_hits"] / max(stats["cache_kv_hits"] + stats["cache_kv_misses"], 1)
)
# savings > 0 and kv_hit_rate > 0.5 means Surface B is actively reducing costsIf compress_runs is 0 after several sessions, compression is not being triggered — check daemon config and whether slm_compress is being called.
If cache_kv_hits does not grow after repeated work, verify key naming consistency (the same key string must be used for set and get, by the same agent).
slm status [--json] [--verbose]Reports system-level state — not optimization counters. Canonical fields:
a, b or c)none--verbose / -v adds: the disabled marker, last booted version, and daemon port.
--json prints the standard envelope {"success", "command", "version", "data": {...}}; read the fields above from data. Prefer it for agent consumption:
slm status --json{"success":true,"command":"status","version":"...","data":{"mode":"a","provider":"none","profile":"default","db_size_mb":12.4,"fact_count":384,"entity_count":201,"edge_count":519,"profile_generation":0,"projection_queue_depth":0,"saves_waiting":0,"unreadable_saves":0}}The MCP equivalent is get_status(profile_id=""), which returns the same fields at the top level (it is not part of the smallest core tool set). saves_waiting above zero means saved memories are durable but still being indexed (searchable within seconds). unreadable_saves above zero means that many saves could not be read back with this computer's key and were kept unchanged in the admission journal (the daemon log has their ids); a negative value means the journal did not answer. Status does not report a user role.
Do not rely on the human-readable format for parsing — always use --json when the output feeds another tool.
slm doctor [--json] [--quick] [--deep] [--fix]Preflight check covering dependencies, embedding worker, daemon connectivity, and Surface B health. The "Optimize (Surface B)" line confirms whether the compression and cache subsystem initialised correctly.
--quick skips the daemon and embedding probes — runs only dependency and config checks; faster but incomplete.
--deep reads every database page (PRAGMA integrity_check) instead of the structural check; slow on a large store. --fix repairs what it can (re-downloads missing models, installs sqlite-vec) before checking, then reports.
--json outputs structured results per check — use this in automated health pipelines.
A passing doctor output confirms:
A failing "Optimize (Surface B)" line means slm_compress, slm_cache_set, and slm_cache_get may not function correctly — investigate daemon config before relying on those tools.
slm optimize status [--json]Shows whether the Optimize module (cache + compress) is currently enabled or disabled at the daemon level. Available subcommands also include optimize on, optimize off, and optimize savings.
The optimize savings subcommand accepts:
slm optimize savings [--since <days>] [--provider anthropic|openai|gemini] [--json]--since defaults to 7 days. --provider filters by the target AI provider.
slm_optimize_stats() via MCP is the same data as slm optimize savings; use whichever surface you have.
slm db integrity [--pages] [--json] # read-only, safe while SLM runs
slm db repair [--json] # preview of what a repair would do (read-only)
slm db repair --apply --root <data folder> [--batch-size N] [--pause-ms MS] [--max-seconds S]
slm db repair --undo <run_id> --root <data folder>
slm ops list | status | resolve <operation_id> --action retry|force_reconcile|cancel
slm brain status [--json] # observation-only Living Brain evidence totals
slm embedder status # progress of an embedding-model switch
slm models # recommended and installed local modelsslm db integrity answers five separate questions so one cannot hide another:
page integrity (only with --pages), relational integrity (orphan rows, erased
words still stored), source fidelity (facts withheld from answers or no longer
saying what their memory said), projection readiness (keyword, vector and date
search work still owed), and any repair running or last run. It prints counts
only, never memory text.
slm db repair fixes leftover rows, erased-word leftovers, unfinished deletes
and memories that lost their searchable fact, with receipts and an undo. It
previews by default; --apply and --undo insist on --root naming the data
folder you mean, and refuse any other. A repair never brings back anything that
was erased, deleted or withheld. slm ops lists failed, stuck or degraded
operations and, for an owner or admin, resolves them. The MCP counterpart for
Living Brain totals is get_brain_evidence_status(profile_id=""); it only
observes and does not change recall, ranking or review.
slm doctor --json at session start to confirm all subsystems are up.slm_optimize_stats() after a batch of work to check token savings.slm status --json when you need DB size or memory counts.ok: false on any MCP tool — check note field, then run slm doctor to isolate the failure.slm db integrity before concluding anything.slm_optimize_stats() never raises. On internal error it returns ok: false with all counters at 0. Continue the session — stats unavailability does not affect compression or caching operations.
slm status --json reports the active profile in data.profile. Use it to confirm which workspace is active before starting work on a multi-profile setup. get_status(profile_id="<name>") counts another profile without moving the active one. To change the active profile, see slm-profile.
slm-session — session lifecycle (session_init/close_session)slm-profile — workspace isolation and profile switchingslm-cache — KV cache performance metricsslm-compress — reversible context compressionSuperLocalMemory v4.1.24 · Qualixar · AGPL-3.0-or-later
© qualixar, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in plugin/skills/slm-status of qualixar/superlocalmemory.
Open the folder on GitHubat commit 26f8c68
Slm Status 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 |
|---|---|---|---|---|---|---|
| Slm Status this skillqualixar/superlocalmemory | 231 | — | ~2.4k | Automated safety check: Notes | AGPL-3.0 | |
| MCP Server Builderanthropics/skills | 180k | 63 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Hook Development for Claude Code Pluginsanthropics/claude-plugins-official | 38k | 10 repos | ~4.1k | Automated safety check: Notes | Apache-2.0 | |
| Using Superpowersfarm-fe/farm | 5.6k | 35 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Executing Plans Inlineobra/superpowers | 297k | 2 repos | ~5.1k | Automated safety check: Pass | MIT | |
| Skill CreatorAzure/azqr | 795 | 89 repos | ~8.2k | Automated safety check: Pass | Apache-2.0 |
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
anthropics/claude-plugins-official
Explains how to write Claude Code plugin hooks, both prompt-based checks and bash commands, for events such as PreToolUse, Stop and SessionStart.
farm-fe/farm
A skill your agent uses when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
obra/superpowers
Has the agent carry out an implementation plan itself, task by task in the current session, keeping a ledger, proving each step with a test and ending with one whole-branch review.
Azure/azqr
Create new skills, modify and improve existing skills, and measure skill performance.
anthropics/claude-plugins-official
Explains how to write agents for Claude Code plugins: the markdown file with YAML frontmatter, trigger descriptions, model and color settings, and system prompt design.
qualixar/superlocalmemory
AI agent memory with mathematical foundations. An agent skill from qualixar/superlocalmemory.
qualixar/superlocalmemory
Index and query a codebase as a structural graph — build the code graph, trace blast radius of a change, find callers/callees/inheritors, semantic code search by meaning, assemble PR review context…
qualixar/superlocalmemory
Gate-verified bounded loops with SuperLocalMemory as the durable ledger.
qualixar/superlocalmemory
Search and retrieve facts, decisions, and past context from SuperLocalMemory.
qualixar/superlocalmemory
Capture durable facts, decisions, constraints, and gotchas into SuperLocalMemory.
qualixar/superlocalmemory
Controls memory visibility across profiles — personal (private, default), shared (selected profiles), or global (all profiles on this machine).
Categories
Health and optimization stats for SuperLocalMemory — call slmoptimizestats() for live compression and cache counters (compressruns, tokenssavedcompress, cacheproxyhits, cacheproxymisses…. Slm Status is an agent skill from qualixar/superlocalmemory. Health and optimization stats for SuperLocalMemory — call slmoptimizestats() for live compression and cache counters (compressruns, tokenssavedcompress, cacheproxyhits, cacheproxymisses, cachekvhits, cachekvmisses); run slm status [--json] for system state (mode, profile, DB size, fact/entity/edge counts) and slm doctor [--json] for preflight including the "Optimize (Surface B)" health line; use together to confirm optimization is actually saving tokens.
Slm Status fits situations like: agent Workflows work in your project.
Run `npx skills add qualixar/superlocalmemory --skill slm-status -a claude-code`. Or copy the skill folder (plugin/skills/slm-status in qualixar/superlocalmemory) into .claude/skills/slm-status in your project. Claude Code loads it when a task matches its description.
Run `npx skills add qualixar/superlocalmemory --skill slm-status -a codex`. Or copy the skill folder (plugin/skills/slm-status in qualixar/superlocalmemory) into .agents/skills/slm-status 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 qualixar/superlocalmemory --skill slm-status -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/slm-status, .gemini/skills/slm-status, .github/skills/slm-status and .opencode/skills/slm-status in your project.
SKILL.md names no scripts, command-line tools or credentials: Slm Status is instructions for the agent only. Our summary lists: Python 3. Its frontmatter pre-approves these tools: slm_optimize_stats, get_status, get_brain_evidence_status, Bash.
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 notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Slm Status is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.4k tokens (SKILL.md is roughly 9.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Slm Status: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 297k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
qualixar (a GitHub organization) maintains it in qualixar/superlocalmemory, which has 231 GitHub stars. The repository holds 17 skills in this directory. The repository was last updated on October 9, 2026.
Source: qualixar/superlocalmemory on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.