query-memory

query-memory is a skill for Claude Code, Codex from Renzo-Tognella/DecisionsSearch. It costs 112 tokens per session (1,989 once invoked), scanned A, original, MIT.

A memory search tool for finding past pull requests, business rules, architecture decisions, coding patterns, features, and reasoning. It can filter results and rank them against a question written in ordinary language.

In plain words
What is it for?
Investigating a project, module, file, topic, pull request, or work item, including questions about previous changes and stored rules.
Why use it?
It helps answer whether similar work was done before and what changed without guessing from incomplete context.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Investigating a project, module, file, topic, pull request, or work item, including questions about previous changes and stored rules.

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Install with agentmods
npx agentmods add skills/renzo-tognella/decisionssearch/query-memory
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.

Any agent
npx skills add Renzo-Tognella/DecisionsSearch --skill query-memory
Clone the repo
git clone --depth 1 https://github.com/Renzo-Tognella/DecisionsSearch

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for query-memory

README.md
[![agentmods](https://agentmods.dev/badge/skills/renzo-tognella/decisionssearch/query-memory.svg)](https://agentmods.dev/skills/renzo-tognella/decisionssearch/query-memory)
Your own site
<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>
Per session 112 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,989 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00112 $0.01989
Opus 5 $0.00056 $0.00994
Sonnet 5 $0.00022 $0.00398
Haiku 4.5 $0.00011 $0.00199

Measured 7d ago against content hash 92f2f79f41d4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

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.

skills-memory/query-memory/SKILL.md · 152 lines

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:

  1. normalizar o caminho para repo-relative;
  2. executar memory.pr.query com changed_file_contains e filtros de projeto/repo quando disponíveis;
  3. conservar todos os candidatos e todos os seus changed_files;
  4. reranquear pela aderência da pergunta ao summary, objetivo e narrativa FeatureDescription, priorizando intenção e efeito operacional;
  5. expandir para BusinessRule, ArchitecturalDecision ou CodePattern somente por links/evidência.

Read the full file on GitHub · 152 lines

Files

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.

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. 7d ago First seen · 152 lines · 112 tokens per session scan A 92f2f79f41d4

Subscribe to this mod's changes

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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