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 Renzo-Tognella/DecisionsSearch --skill query-memorygit clone --depth 1 https://github.com/Renzo-Tognella/DecisionsSearchWrote 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/renzo-tognella/decisionssearch/query-memory)<a href="https://agentmods.dev/skills/renzo-tognella/decisionssearch/query-memory"><img src="https://agentmods.dev/badge/skills/renzo-tognella/decisionssearch/query-memory.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 | $0.00112 | $0.01989 |
| Opus 5 | $0.00056 | $0.00994 |
| Sonnet 5 | $0.00022 | $0.00398 |
| Haiku 4.5 | $0.00011 | $0.00199 |
Grade A, and why
query-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 7d 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Query Memory
Você é a interface de busca do grafo: recupera PRMemories operacionais, narrativas FeatureDescription, BusinessRules, ArchitecturalDecisions, CodePatterns e reasoning. A resposta é sustentada apenas pelos nós retornados e pelos links que foram realmente verificados.
CORE RULE: Se a pergunta nomeia um arquivo, a primeira etapa é busca exata em changed_files e a segunda é reranking pelo summary/objetivo em prosa do PR. Para qualquer pergunta, cite memory_ids e não invente memória, objetivo, regra ou relação.
When to activate
- Trigger phrases: "já fizemos algo assim?", "o que mudou no módulo X?", "busca na memória", "tem regra sobre Y?", "o que mudou nesse arquivo?"
- Contexts: início de task nova; investigação por tema, projeto, módulo, domínio, arquivo, repo, PR ou work item
Do NOT activate for:
- "como essa regra chegou nesse estado?" → use rule-blame
- "por que a arquitetura/tecnologia X?" → use architecture-blame
- "por que esse arquivo é assim?" → use code-blame
- criar/capturar memórias → use decisionssearch-capture ou as create-*
Inputs
- question (required): pergunta em linguagem natural. Fonte: usuário.
- filters (optional): projeto, classe, módulo/domínio, repo, pr_number, arquivo, work item. Fonte: pergunta + taxonomia.
Context load
- Carregar .decisionssearch/business.md; a taxonomia traduz termos em módulos/domínios.
- Se o arquivo não existir → seguir sem filtro de taxonomia, avisando.
- Verificar MCP DecisionsSearch com um memory.query trivial.
Contrato de busca
Pergunta com arquivo
Use obrigatoriamente esta ordem:
- normalizar o caminho para repo-relative;
- executar memory.pr.query com changed_file_contains e filtros de projeto/repo quando disponíveis;
- conservar todos os candidatos e todos os seus changed_files;
- reranquear pela aderência da pergunta ao summary, objetivo e narrativa FeatureDescription, priorizando intenção e efeito operacional;
- expandir para BusinessRule, ArchitecturalDecision ou CodePattern somente por links/evidência.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 152 lines · 112 tokens per session scan A 92f2f79f41d4
query-memory is a skill published in the GitHub repository Renzo-Tognella/DecisionsSearch (0 stars, last pushed 14d ago), licensed MIT. It adds 112 tokens to every session and 1,989 once invoked, about $0.0006 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 2026-08-31.
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