Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/felvieira/claude-skills-fvnpx agentmods add commands/felvieira/claude-skills-fv/consolidate-memoryWrote 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/commands/felvieira/claude-skills-fv/consolidate-memory)<a href="https://agentmods.dev/commands/felvieira/claude-skills-fv/consolidate-memory"><img src="https://agentmods.dev/badge/commands/felvieira/claude-skills-fv/consolidate-memory/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/commands/felvieira/claude-skills-fv/consolidate-memory"><img src="https://agentmods.dev/badge/commands/felvieira/claude-skills-fv/consolidate-memory.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 | $0.00035 | $0.02171 |
| Opus 5 | $0.00017 | $0.01086 |
| Sonnet 5 | $0.00007 | $0.00434 |
| Haiku 4.5 | $0.00003 | $0.00217 |
Grade A, and why
consolidate-memory scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/consolidate-memory — Manutenção do Vault de Memória
Objetivo: rotina de manutenção do vault persistente seguindo policies/memory-consolidation.md. Workflow seguro: snapshot → dry-run → confirmação → apply → verify → report.
Quando usar:
- semanalmente (rotina)
- após uso intenso (50+ sessions)
- antes de release major (limpar stale)
- vault crescer demais (> 500 arquivos)
Quando NÃO usar:
- vault recém-criado (< 20 arquivos)
- sem backup possível (não é repo git, não tem espaço para
.bak)
Skill ativada: Context Manager (skill 08) em modo "vault janitor".
Pré-requisitos
- vault em
D:\claude-memory\ou path explícito via--vault <path> - backup viável (espaço em disco para snapshot OU vault é repo git)
Processo
Passo 1 — Snapshot
VAULT="${1:-D:/claude-memory}"
TIMESTAMP=$(date +%Y-%m-%d-%H%M)
# Se é repo git: commit
if [ -d "$VAULT/.git" ]; then
cd "$VAULT" && git add -A && git commit -m "snapshot pre-consolidate $TIMESTAMP"
else
# Copy snapshot
cp -r "$VAULT" "$VAULT.bak.$TIMESTAMP"
fi
Passo 2 — Dry run (auditoria sem mudança)
Para cada categoria de policies/memory-consolidation.md, listar candidatos:
2.1 Logs de sessão duplicados
- Buscar logs do mesmo dia/projeto:
ls $VAULT/logs/YYYY-MM-DD-<projeto>-*.md - Comparar similaridade (filename ou conteúdo > 80% similar) → marcar para merge
- Output: lista de pares
[A.md, B.md] → keep A, delete B
2.2 Logs órfãos / antigos
- Logs > 90 dias sem ser referenciado em outro lugar → archive candidate
- Logs de projetos inexistentes → archive candidate
2.3 Architecture decisions
- Decisões com mesmo título em projetos iguais → merge candidate
- Decisões
status: supersededsem newer ref → flag
2.4 Working set / context packs
- Files referenciados que não existem mais → remove entry
- Entries duplicadas (mesmo path) → merge metadata
2.5 Learned skills
- Score < 0.3 e idade > 30d → archive candidate
- Score ≥ 0.8 e 5+ usos → promote candidate
- Triggers conflitantes → resolve candidate
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.
- 12d ago First seen · 224 lines · 35 tokens per session scan A 11b1ff8b328b
consolidate-memory is a command published in the GitHub repository felvieira/claude-skills-fv (23 stars, last pushed today), licensed Apache-2.0. It adds 35 tokens to every session and 2,171 once invoked, about $0.0002 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.
Other commands, from other repositories
session-end
I'll summarize this coding session and update the memory system with our accomplishments.
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
memory-store
Store an insight, decision, or pattern to memory.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.