Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ardiannurcahya/ogm-mcp-skills --skill resourcesgit clone --depth 1 https://github.com/ardiannurcahya/ogm-mcp-skillsWrote 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/ardiannurcahya/ogm-mcp-skills/resources)<a href="https://agentmods.dev/skills/ardiannurcahya/ogm-mcp-skills/resources"><img src="https://agentmods.dev/badge/skills/ardiannurcahya/ogm-mcp-skills/resources/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ardiannurcahya/ogm-mcp-skills/resources"><img src="https://agentmods.dev/badge/skills/ardiannurcahya/ogm-mcp-skills/resources.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00064 | $0.03314 |
| Opus 5.5 | $0.00026 | $0.01326 |
| Sonnet 5.5 | $0.00013 | $0.00663 |
| Haiku 4.5 | $0.00006 | $0.00331 |
Grade A, and why
ogm scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
* **NEVER** run `curl` commands to `/v1/...` API endpoints manually. How it starts
The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenGraphMemory (OGM) Skill
This skill provides a comprehensive, unambiguous, production-grade operational guide for AI Agents interacting with OpenGraphMemory (OGM). It covers four core capabilities:
- Hybrid RAG & Semantic Retrieval (Dense Vector pgvector + Knowledge Graph traversal via RRF).
- Codebase AST Call-Graphs & Centrality (Tree-sitter continuous AST extraction).
- Document Knowledge Graphs & Evidence Citations (LiteParse verbatim text & spatial bounding boxes).
- Persistent Failure-Driven Agent Operational Memory (Bayesian confidence, closed-loop feedback, supersession).
⚡ Agent Lifecycle Trigger Matrix
Follow this 4-phase protocol during all pair-programming and engineering sessions:
| Phase | Agent State / Event | Mandatory Action | Primary MCP Tool |
|---|---|---|---|
| 1. Inception & Recall | User asks to fix a bug, diagnose an error, refactor, or query system architecture. | Search prior memory first to check if a verified solution exists. Query Hybrid RAG for architecture context. | ogm_recall_code_memoryogm_memory_searchogm_retrieval_query |
| 2. Blast Radius & Navigation | Agent explores codebase structure before modifying code. | Search AST symbols (functions/classes) and trace caller/callee relationships to evaluate impact. | ogm_search_code_symbolsogm_get_code_call_graphogm_get_code_chunks |
| 3. Live Code Sync | Agent edits or writes a code file during pair-programming. | Sync single-file AST into Knowledge Graph in real-time (<15ms). | ogm_sync_code_file |
| 4. Persistence & Closure | Bug is fixed, tests pass, migration succeeds, or PR is merged. | Record verified outcome & lesson so future agent sessions don't repeat the error. | ogm_record_code_fixogm_memory_record_outcome |
🎯 Task Intent Routing (English & Indonesian Triggers)
🔍 Category 1: Hybrid RAG & Semantic Retrieval
English Triggers:
- "How does the authentication / payment / storage service work?"
- "Query documentation and code using Hybrid RAG"
- "Find relevant evidence and quotes for architecture spec X"
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.
- 1mo ago Changed · +35 lines · +4 tokens per session 1aa792f2ae22
- 1mo ago First seen · 189 lines · 60 tokens per session scan A d651271247fe
ogm is a skill published in the GitHub repository ardiannurcahya/ogm-mcp-skills (4 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 3,314 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
init-workspace-documentation
Skill "init-workspace-documentation" from griddynamics/rosetta, covering agent memory.md, agent memory, preventive rules, what worked and what failed.
memorix-mini-skills
Use when durable project knowledge, gotchas, workflows, or repeated fixes should become reusable agent guidance instead of ordinary memory.
memorix-sessions
Use when resuming work, preparing handoff context, binding an HTTP control-plane project, or deciding whether sessionstart is useful.
frontmcp-extensibility
Use when extending FrontMCP beyond the core SDK by integrating external npm packages, libraries, or third-party services into providers and tools. Covers VectoriaDB for in-memory semantic and vector search (ML-based embeddings or TF-IDF keyword engines, with persistence) and the tamper-evident, hash-chained skill…
memory-audit-pattern-extraction
A method for investigating repeated mistakes by comparing related memories and checking whether an earlier reminder failed. It looks at where the reminder was stored, when it was created, and whether it was strong enough to prevent the mistake.
frontmcp-testing
Use for anything about testing FrontMCP servers: writing or running unit, integration, and E2E tests and reaching the 95%+ coverage bar. Covers Jest setup and coverage gating; unit-testing a ToolContext execute() with mock context, inputs, and Zod schema validation; testing resources and prompts; in-memory testing via…