mcp-memory-service is a self-hosted memory backend that lets AI agents store and retrieve shared project context through REST, MCP, OAuth, a command-line interface, and a dashboard. It is intended for agent pipelines and clients such as LangGraph, CrewAI, AutoGen, Claude Desktop, and OpenCode, with support for knowledge graphs and memory consolidation. The catalogue includes skills, agents, commands, instructions, hooks, a setting, an MCP entry, and a plugin for its workflows.
Borrowing it
Nothing to install: this file belongs to doobidoo/mcp-memory-service. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/doobidoo/mcp-memory-service/main/.claude/skills/gitnexus-refactoring/SKILL.mdgit clone --depth 1 https://github.com/doobidoo/mcp-memory-serviceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/doobidoo/mcp-memory-service/gitnexus-refactoring)<a href="https://agentmods.dev/skills/doobidoo/mcp-memory-service/gitnexus-refactoring"><img src="https://agentmods.dev/badge/skills/doobidoo/mcp-memory-service/gitnexus-refactoring.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00016 | $0.00996 |
| Opus 5 | $0.00008 | $0.00498 |
| Sonnet 5 | $0.00003 | $0.00199 |
| Haiku 4.5 | $0.00002 | $0.00100 |
Grade A, and why
gitnexus-refactoring scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
80% identical to gitnexus-refactoring — 76 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Refactoring with GitNexus
When to Use
- "Rename this function safely"
- "Extract this into a module"
- "Split this service"
- "Move this to a new file"
- Any task involving renaming, extracting, splitting, or restructuring code
Workflow
1. gitnexus_impact({target: "X", direction: "upstream"}) → Map all dependents
2. gitnexus_query({query: "X"}) → Find execution flows involving X
3. gitnexus_context({name: "X"}) → See all incoming/outgoing refs
4. Plan update order: interfaces → implementations → callers → tests
If "Index is stale" → run
npx gitnexus analyzein terminal.
Checklists
Rename Symbol
- [ ] gitnexus_rename({symbol_name: "oldName", new_name: "newName", dry_run: true}) — preview all edits
- [ ] Review graph edits (high confidence) and ast_search edits (review carefully)
- [ ] If satisfied: gitnexus_rename({..., dry_run: false}) — apply edits
- [ ] gitnexus_detect_changes() — verify only expected files changed
- [ ] Run tests for affected processes
Extract Module
- [ ] gitnexus_context({name: target}) — see all incoming/outgoing refs
- [ ] gitnexus_impact({target, direction: "upstream"}) — find all external callers
- [ ] Define new module interface
- [ ] Extract code, update imports
- [ ] gitnexus_detect_changes() — verify affected scope
- [ ] Run tests for affected processes
Split Function/Service
- [ ] gitnexus_context({name: target}) — understand all callees
- [ ] Group callees by responsibility
- [ ] gitnexus_impact({target, direction: "upstream"}) — map callers to update
- [ ] Create new functions/services
- [ ] Update callers
- [ ] gitnexus_detect_changes() — verify affected scope
- [ ] Run tests for affected processes
Tools
gitnexus_rename — automated multi-file rename:
gitnexus_rename({symbol_name: "validateUser", new_name: "authenticateUser", dry_run: true})
→ 12 edits across 8 files
→ 10 graph edits (high confidence), 2 ast_search edits (review)
→ Changes: [{file_path, edits: [{line, old_text, new_text, confidence}]}]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 114 lines · 16 tokens per session scan A ffbfe81939aa
gitnexus-refactoring is a skill published in the GitHub repository doobidoo/mcp-memory-service (1,926 stars, last pushed today), licensed Apache-2.0. It adds 16 tokens to every session and 996 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 80% identical to gitnexus-refactoring, differing in 76 lines, and is treated as a copy.
Other skills, from other repositories
compartmentalize
Sweep this conversation and save everything potentially worth knowing again into Compartment, the encrypted memory vault. Run it before compacting or summarizing so nothing is lost to the summary, or on its own at any point to bank the session.
memwal
Walrus Memory SDK — portable agent memory that works across apps, sessions, and workflows. Use when users say: "add memory to my app" "portable agent memory" "integrate Walrus Memory" "AI agent memory" "memory across agents" "Walrus memory storage" "setup Walrus Memory" "recall memories".
chroma
Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source…
lilbee-mcp
Search and manage the user's local lilbee knowledge base over MCP. Use whenever the user has indexed code, docs, PDFs, or web pages into lilbee and you need cited answers, or whenever they ask you to ingest content, swap models, or tune retrieval against their library. Every fact returned cites file and line.…
notebrain-assistant
Search and explore an Obsidian vault through the NoteBrain CLI (semantic search, tags, backlinks, connections, hidden links, boosted retrieval). Use it whenever the user mentions their notes, knowledge base, Obsidian vault, semantic search, finding connections or unlinked notes, or asks exploratory questions like…
palaia-memory
Check this person's shared memory before answering anything about their own work, and add to it when something is worth keeping. It holds their projects, decisions and reasons, house conventions (naming, commit messages, tests, releases, review and escalation), people and hard-won details, and every AI tool they use…