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 build-with-dhiraj/ai-workflow-framework-portability-kit --skill memory-routergit clone --depth 1 https://github.com/build-with-dhiraj/ai-workflow-framework-portability-kitWrote 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/build-with-dhiraj/ai-workflow-framework-portability-kit/memory-router)<a href="https://agentmods.dev/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/memory-router"><img src="https://agentmods.dev/badge/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/memory-router/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/build-with-dhiraj/ai-workflow-framework-portability-kit/memory-router"><img src="https://agentmods.dev/badge/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/memory-router.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 | $0.00136 | $0.02869 |
| Opus 5.5 | $0.00054 | $0.01148 |
| Sonnet 5.5 | $0.00027 | $0.00574 |
| Haiku 4.5 | $0.00014 | $0.00287 |
Grade A, and why
memory-router 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 29d 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.
How it starts
The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Router
Decides where new content belongs in D Rage's JoVE knowledge system: Obsidian vault (RAM) for what changes, Pinecone (jove-memory index) for what doesn't. Apply this BEFORE writing any new artifact — not after.
The one routing rule
Ask: "Will this be edited again?"
- Yes → Obsidian vault (RAM)
- No → Pinecone
jove-memory(HD)
That's it. Everything below is tiebreakers and namespace-routing for when the answer isn't obvious.
Why this rule works
Obsidian and Pinecone are complementary, not competing — they serve different cognitive layers:
- Vault = reasoning surface. Mutable. Wiki-linked. Indexed by [[index]] + MOCs. The shape of D's thinking lives here. Every Claude session pays a token tax to load index.md + CLAUDE.md, so the vault should stay lean.
- Pinecone = perfect-recall archive. Immutable. Semantic search via E5 embeddings. Cost is flat regardless of size. Conversations, books, meetings, deep-research snapshots — everything that happened but isn't current belongs here.
Mixing them fails both ways: if you put archive content in the vault, the wiki bloats and the token tax grows linearly with content volume. If you put active strategy in Pinecone, you lose the wiki-link graph that makes reasoning possible.
Tiebreakers (apply in order when "Will this be edited again?" is ambiguous)
- Will it be searched semantically? ("Find anything we ever discussed about X.") → Pinecone. Vector search is the point.
- Will it be wiki-linked from MOCs or other notes? → Vault. The graph is the value.
- Is it a snapshot of state on a specific date? (e.g., "as of 2026-05-23, competitor X has Y features") → Pinecone with
as_ofmetadata. - Does it represent the current authoritative position? (e.g., "this is the PI persona we're going with") → Vault.
- Is it >2,000 words? → Strongly consider Pinecone chunking. Vault notes >2K words become unreadable.
- Does the user need to edit it by hand in Obsidian? → Vault.
- Is it generated by a deep-research / book-digest / meeting-transcript flow? → Pinecone (default for these flows).
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.
- 29d ago First seen · 160 lines · 136 tokens per session scan A ac3c7de107f7
memory-router is a skill published in the GitHub repository build-with-dhiraj/ai-workflow-framework-portability-kit (5 stars, last pushed 16d ago), licensed MIT. It adds 136 tokens to every session and 2,869 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-21.
Other skills, from other repositories
agents-md-improver
Audit and improve project-rules files (AGENTS.md, CLAUDE.md, .agents/instructions, local overrides) so the agent keeps accurate project context. Use when the user asks to check, audit, review, update, improve, or fix their AGENTS.md or CLAUDE.md, mentions "project rules maintenance" or "agent context optimization", or…
agents-md-revise
Capture learnings from the current session into the project-rules file (AGENTS.md, CLAUDE.md, or local override) so future sessions benefit. Use when the user says "revise the rules", "update AGENTS.md / CLAUDE.md with what we just learned", "save this to project memory", "remember this for next time", or at the end…
hf-cloud-serving-image-selection
Select and verify the current region-specific serving container URI for a SageMaker model deployment. Use after the deployment pathway is chosen and before endpoint code; never infer an image URI from memory.
pith-wiki
Wiki mode — persistent knowledge base maintenance. Active during /pith wiki mode. Defines page formats, ingest workflow, query workflow, and lint checks.
hf-mem
Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub.
pith-setup
Pith onboarding conversation. Runs on first session in a new project. Introduces Pith, offers wiki setup, guides through initialization. Injected by session-start.js when no prior setup detected.