v-memory-refresh

A command that refreshes a local offline search index of documentation; FTS5 is a built-in SQLite feature for full-text search.

In plain words
What is it for?
Use it after pulling new documents, to check index health, or—when explicitly enabled—to build and refresh embedding-based search data.
Why use it?
It keeps the local memory cache current after documentation changes and can optionally add semantic search embeddings.

Command

Install

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.

agentmods
npx agentmods add commands/procoders/superpowers-v/v-memory-refresh
Clone the repo
git clone --depth 1 https://github.com/procoders/superpowers-v
Per session 65 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 445 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00065 $0.00445
Opus 5 $0.00032 $0.00222
Sonnet 5 $0.00013 $0.00089
Haiku 4.5 $0.00006 $0.00044

Measured 2d ago against content hash bf8eeda21bb8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

v-memory-refresh 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 2d 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.

commands/v-memory-refresh.md · 34 lines

What it actually says

You are running /v:memory-refresh. Args: {{args}}.

Default — offline, FTS5, no install, no network:

python3 scripts/compound-v-memory.py refresh
python3 scripts/compound-v-memory.py doctor

Report the doctor summary (files / chunks / staleness / whether embeddings are bootstrapped).

Semantic lane (opt-in). Embeddings are OFF by default and live outside the repo (~/.cache/compound-v/memory/<repo-id>/). Enabling them is the only step that touches the network — and it must be explicit, never from a hook:

python3 scripts/compound-v-memory.py bootstrap                 # creates the out-of-repo venv + model (one time)
python3 scripts/compound-v-memory.py refresh --with-embeddings # populate vectors

If the project opted into embeddings at /v:init (memory.embeddings: true in .claude/compound-v.json), the engine already adds vectors on a plain refresh once bootstrapped — you don't need the flag. If {{args}} asks for --with-embeddings and doctor shows embeddings are not bootstrapped, run bootstrap first (tell the user it will download a ~200 MB model once). The semantic lane is scale-gated: it only changes ranking once the corpus is large enough to matter; on a small corpus FTS5 already wins. If bootstrap fails (offline / no wheels), the engine stays FTS5-only — recall still works. See skills/compound-v/memory.md.

Changes

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.

  1. 2d ago First seen · 34 lines · 65 tokens per session scan A bf8eeda21bb8

Subscribe to this mod's changes

v-memory-refresh is a command published in the GitHub repository procoders/superpowers-v (35 stars, last pushed 3d ago), licensed MIT. It adds 65 tokens to every session and 445 once invoked, about $0.0003 per session on Opus 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 2026-08-30.