memory-query-workflow

memory-query-workflow is a skill for Claude Code from yeaight7/agent-powerups. It costs 33 tokens per session (522 once invoked), scanned A, original, Apache-2.0.

A procedure for retrieving information from a previously built knowledge graph. It chooses a lookup, connection trace, or concept explanation based on the question and checks whether the graph is still current.

In plain words
What is it for?
Use it for questions about connected concepts, relationships between systems or files, explanations of graph nodes, and deciding when to rebuild or update stored memory.
Why use it?
It helps avoid starting broad file exploration when reusable graph information is available. It also handles missing, stale, sparse, or weak graph results explicitly.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the memory-optimization plugin — 6 skills, 3 commands, 2 agents shipped together

Good fit Use it for questions about connected concepts, relationships between systems or files, explanations of graph nodes, and deciding when to rebuild or update stored memory.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yeaight7/agent-powerups/memory-query-workflow
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 yeaight7/agent-powerups --skill memory-query-workflow
Clone the repo
git clone --depth 1 https://github.com/yeaight7/agent-powerups

Made for: Claude Code.

Or install memory-optimization, the plugin that ships this one along with the rest of its 6 skills, 3 commands, 2 agents.

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 memory-query-workflow

README.md
[![agentmods](https://agentmods.dev/badge/skills/yeaight7/agent-powerups/memory-query-workflow/github.svg)](https://agentmods.dev/skills/yeaight7/agent-powerups/memory-query-workflow)
Your own site
<a href="https://agentmods.dev/skills/yeaight7/agent-powerups/memory-query-workflow"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/memory-query-workflow/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.

agentmods 80×15 button for memory-query-workflow

Your own site · 80×15
<a href="https://agentmods.dev/skills/yeaight7/agent-powerups/memory-query-workflow"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/memory-query-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 522 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 $0.00033 $0.00522
Opus 5 $0.00016 $0.00261
Sonnet 5 $0.00007 $0.00104
Haiku 4.5 $0.00003 $0.00052

Measured yesterday against content hash 5f1b98619921, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-15, from the pricing page.

Security

Grade A, and why

memory-query-workflow 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 yesterday.

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.

plugins/memory-optimization/skills/memory-query-workflow/SKILL.md · 67 lines

How it starts

The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Memory Query Workflow

Overview

Use existing graph memory first.

Query the graph before rereading source files unless the graph is missing, stale, or too weak for the question.

Required Check

apx check graphify

Required State

  • existing graphify-out/graph.json

Routing

Question shape Action
broad question about connected concepts graphify query
trace between two concepts, files, or systems graphify path
explain one concept or node in context graphify explain
no graph exists switch to memory-build-workflow
graph exists but corpus changed recommend graphify --update before trusting results

Core Rules

  • prefer graph retrieval over full-corpus reread
  • say explicitly when the graph is missing, stale, sparse, or weakly matched
  • do not overclaim beyond what graph nodes and edges support
  • when graph coverage is weak, use the graph result to target the next direct read instead of restarting broad exploration

Minimal Workflow

  1. Confirm graphify-out/graph.json exists.
  2. Choose query, path, or explain based on question shape.
  3. Answer from graph evidence first.
  4. If result quality is weak, say why: missing graph, stale graph, low coverage, or weak node match.
  5. Escalate to build/update or targeted reread only when needed.

Common Failure Modes

  • skipping graph lookup and rereading everything
  • hiding that the graph is stale or incomplete
  • using query for a question that clearly needs a path trace
  • treating no-result output as proof the corpus lacks the concept

Verification

  • Graph existence was confirmed before any query ran
  • The command matched the question shape: query for breadth, path for traces, explain for one node
  • The answer is grounded in graph nodes and edges — no overclaiming
  • Staleness, sparseness, or weak node matches were stated explicitly
  • Escalation to build, update, or targeted reread happened only when graph evidence was insufficient

Read the full file on GitHub · 67 lines

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. yesterday First seen · 67 lines · 33 tokens per session scan A 5f1b98619921

Subscribe to this mod's changes

memory-query-workflow is a skill published in the GitHub repository yeaight7/agent-powerups (6 stars, last pushed 2d ago), licensed Apache-2.0. It adds 33 tokens to every session and 522 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 2026-09-14.